Are you over 18 and want to see adult content?
More Annotations
A complete backup of fuji-keizai.co.jp
Are you over 18 and want to see adult content?
A complete backup of sandrpcrepair.com
Are you over 18 and want to see adult content?
A complete backup of agrigentonotizie.it
Are you over 18 and want to see adult content?
A complete backup of foodanddrinkguides.co.uk
Are you over 18 and want to see adult content?
A complete backup of humptydumptyfrumpty.com
Are you over 18 and want to see adult content?
A complete backup of yazaki-europe.com
Are you over 18 and want to see adult content?
Favourite Annotations
A complete backup of https://benculzang.com
Are you over 18 and want to see adult content?
A complete backup of https://mentormate.com
Are you over 18 and want to see adult content?
A complete backup of https://om4.com.au
Are you over 18 and want to see adult content?
A complete backup of https://fpa2.org
Are you over 18 and want to see adult content?
A complete backup of https://testlio.com
Are you over 18 and want to see adult content?
A complete backup of https://schaubandcompany.com
Are you over 18 and want to see adult content?
A complete backup of https://globalheritagefund.org
Are you over 18 and want to see adult content?
A complete backup of https://birst.com
Are you over 18 and want to see adult content?
A complete backup of https://couch-kimchi.com
Are you over 18 and want to see adult content?
A complete backup of https://mccourier.com
Are you over 18 and want to see adult content?
A complete backup of https://asec.org
Are you over 18 and want to see adult content?
A complete backup of https://robertplant.com
Are you over 18 and want to see adult content?
Text
LEARNING DSP
The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D.FILTER BASICS
Filter Basics. Digital filters are a very important part of DSP. In fact, their extraordinary performance is one of the key reasons that DSP has become so popular. As mentioned in the introduction, filters have two uses: signal separation and signal restoration. Signal separation is needed when a signal has been contaminated withinterference
THE CHEBYSHEV AND BUTTERWORTH RESPONSES The Chebyshev response is an optimal trade-off between these two parameters. When the ripple is set to 0%, the filter is called a maximally flat or Butterworth filter (after S. Butterworth, a British engineer who described this response in 1930). A ripple of 0.5% is a often good choice for digital filters. This matches the typicalprecision and
COMMON IMPULSE RESPONSES Common Impulse Responses. Delta Function. The simplest impulse response is nothing more that a delta function, as shown in Fig. 7-1a. That is, an impulse on the input produces an identical impulse on the output. This means that all signals are passed through the systemwithout change.
SPEED AND PRECISION COMPARISONS where N is the number of points in the DFT and k DFT is a constant of proportionality. If the sine and cosine values are calculated within the nested loops, k DFT is equal to about 25 microseconds on a Pentium at 100 MHz. If you precalculate the sine and cosine values and store them in a look-up-table, k DFT drops to about 7 microseconds. For example, a 1024 point DFT will require about 25 HARMONICS - DSPGUIDE.COM Harmonics. If a signal is periodic with frequency f, the only frequencies composing the signal are integer multiples of f, i.e., f, 2 f, 3 f, 4 f, etc. These frequencies are called harmonics. The first harmonic is f, the second harmonic is 2 f, the third harmonic is 3 f,and so forth.
WINDOWED-SINC FILTERS Windowed-sinc filters are used to separate one band of frequencies from another. They are very stable, produce few surprises, and can be pushed to incredible performance levels. These exceptional frequency domain characteristics are obtained at the expense of poor performance in the time domain, including excessive ripple and overshoot in theCHIRP SIGNALS
Chirp Signals. Chirp signals are an ingenious way of handling a practical problem in echo location systems, such as radar and sonar. Figure 11-9 shows the frequency response of the chirp system. The magnitude has a constant value of one, while the phase is a parabola: The parameter α introduces a linear slope in the phase, that is, itsimply
FREQUENCY RESPONSE
Frequency Response. Figure 15-2 shows the frequency response of the moving average filter. It is mathematically described by the Fourier transform of the rectangular pulse, as discussed in Chapter 11: The roll-off is very slow and the stopband attenuation is ghastly. Clearly, the moving average filter cannot separate one band offrequencies
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNALABOUT THE BOOKSTEVEN W. SMITHERRATAREVIEWSEDITIONSEIGHT GOOD REASONS FORLEARNING DSP
The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D.FILTER BASICS
Filter Basics. Digital filters are a very important part of DSP. In fact, their extraordinary performance is one of the key reasons that DSP has become so popular. As mentioned in the introduction, filters have two uses: signal separation and signal restoration. Signal separation is needed when a signal has been contaminated withinterference
THE CHEBYSHEV AND BUTTERWORTH RESPONSES The Chebyshev response is an optimal trade-off between these two parameters. When the ripple is set to 0%, the filter is called a maximally flat or Butterworth filter (after S. Butterworth, a British engineer who described this response in 1930). A ripple of 0.5% is a often good choice for digital filters. This matches the typicalprecision and
COMMON IMPULSE RESPONSES Common Impulse Responses. Delta Function. The simplest impulse response is nothing more that a delta function, as shown in Fig. 7-1a. That is, an impulse on the input produces an identical impulse on the output. This means that all signals are passed through the systemwithout change.
SPEED AND PRECISION COMPARISONS where N is the number of points in the DFT and k DFT is a constant of proportionality. If the sine and cosine values are calculated within the nested loops, k DFT is equal to about 25 microseconds on a Pentium at 100 MHz. If you precalculate the sine and cosine values and store them in a look-up-table, k DFT drops to about 7 microseconds. For example, a 1024 point DFT will require about 25 HARMONICS - DSPGUIDE.COM Harmonics. If a signal is periodic with frequency f, the only frequencies composing the signal are integer multiples of f, i.e., f, 2 f, 3 f, 4 f, etc. These frequencies are called harmonics. The first harmonic is f, the second harmonic is 2 f, the third harmonic is 3 f,and so forth.
WINDOWED-SINC FILTERS Windowed-sinc filters are used to separate one band of frequencies from another. They are very stable, produce few surprises, and can be pushed to incredible performance levels. These exceptional frequency domain characteristics are obtained at the expense of poor performance in the time domain, including excessive ripple and overshoot in theCHIRP SIGNALS
Chirp Signals. Chirp signals are an ingenious way of handling a practical problem in echo location systems, such as radar and sonar. Figure 11-9 shows the frequency response of the chirp system. The magnitude has a constant value of one, while the phase is a parabola: The parameter α introduces a linear slope in the phase, that is, itsimply
FREQUENCY RESPONSE
Frequency Response. Figure 15-2 shows the frequency response of the moving average filter. It is mathematically described by the Fourier transform of the rectangular pulse, as discussed in Chapter 11: The roll-off is very slow and the stopband attenuation is ghastly. Clearly, the moving average filter cannot separate one band offrequencies
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. WINDOWED-SINC FILTERS Windowed-sinc filters are used to separate one band of frequencies from another. They are very stable, produce few surprises, and can be pushed to incredible performance levels. These exceptional frequency domain characteristics are obtained at the expense of poor performance in the time domain, including excessive ripple and overshoot in the ARCHITECTURE OF THE DIGITAL SIGNAL PROCESSOR Architecture of the Digital Signal Processor. One of the biggest bottlenecks in executing DSP algorithms is transferring information to and from memory. This includes data, such as samples from the input signal and the filter coefficients, as well as program instructions, the binary codes that go into the program sequencer.NARROW-BAND FILTERS
Narrow-band Filters. A common need in electronics and DSP is to isolate a narrow band of frequencies from a wider bandwidth signal. For example, you may want to eliminate 60 hertz interference in an instrumentation system, or isolate the signaling tones in a telephone network. Two types of frequency responses are available: the band-passand
PHASE RESPONSE
Phase Response. There are three types of phase response that a filter can have: zero phase, linear phase, and nonlinear phase. An example of each of these is shown in Figure 19-7. As shown in (a), the zero phase filter is characterized by an impulse response that is symmetrical around sample zero. The actual shape doesn't matter, only that the DESIGNING THE FILTER Recursive filters are designed by first selecting the location of the poles and zeros, and then finding the appropriate recursion coefficients (or analog components). For example, Butterworth filters have poles that lie on a circle in the complex plane, while in a Chebyshev filter they lie on an ellipse. This is the topic of Chapters32 and 33.
CONVOLUTION VIA THE FREQUENCY DOMAIN Figure 9-8 provides an answer: transform the two signals into the frequency domain, multiply them, and then transform the result back into the time domain. This replaces one convolution with two DFTs, a multiplication, and an Inverse DFT. Even though the intermediate steps are very different, the output is identical to the standardconvolution
HUMAN HEARING
Human Hearing. The human ear is an exceedingly complex organ. To make matters even more difficult, the information from two ears is combined in a perplexing neural network, the human brain. Keep in mind that the following is only a brief overview; there are many subtle effects and poorly understood phenomena related to human hearing. MOVING AVERAGE FILTERS The moving average is the most common filter in DSP, mainly because it is the easiest digital filter to understand and use. In spite of its simplicity, the moving average filter is optimal for a common task: reducing random noise while retaining a sharp step response. This makes it the premier filter for time domain encoded signals. JPEG (TRANSFORM COMPRESSION) JPEG (Transform Compression) Many methods of lossy compression have been developed; however, a family of techniques called transform compression has proven the most valuable. The best example of transform compression is embodied in the popular JPEG standard of image encoding. JPEG is named after its origin, the Joint Photographers Experts Group.DECONVOLUTION
Deconvolution. Unwanted convolution is an inherent problem in transferring analog information. For instance, all of the following can be modeled as a convolution: image blurring in a shaky camera, echoes in long distance telephone calls, the finite bandwidth of analog sensors and electronics, etc. Deconvolution is the process offiltering a
THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNALERRATAABOUT THE BOOKEIGHT GOOD REASONS FOR LEARNING DSPREVIEWSSTEVEN W. SMITH The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. CONVOLUTION VIA THE FREQUENCY DOMAIN Figure 9-8 provides an answer: transform the two signals into the frequency domain, multiply them, and then transform the result back into the time domain. This replaces one convolution with two DFTs, a multiplication, and an Inverse DFT. Even though the intermediate steps are very different, the output is identical to the standardconvolution
CIRCULAR BUFFERING
of samples, perform the algorithm, and output a group of samples. This is the world of Digital Signal Processors. Now look back at Fig. 28-2 and imagine that this is an FIR filter being implemented in real-time.To calculate the output sample, we must have access to a certain number of the most recent samples from the input. COMMON IMPULSE RESPONSES Common Impulse Responses. Delta Function. The simplest impulse response is nothing more that a delta function, as shown in Fig. 7-1a. That is, an impulse on the input produces an identical impulse on the output. This means that all signals are passed through the systemwithout change.
THE DIGITAL SIGNAL PROCESSOR MARKET The Digital Signal Processor Market. The DSP market is very large and growing rapidly. As shown in Fig. 28-14, it will be about 8-10 billion dollars/year at the turn of the century, and growing at a rate of 30-40% each year. This is being fueled by the incessant. demand for better and cheaper consumer products, such as: cellular telephones JPEG (TRANSFORM COMPRESSION) JPEG (Transform Compression) Many methods of lossy compression have been developed; however, a family of techniques called transform compression has proven the most valuable. The best example of transform compression is embodied in the popular JPEG standard of image encoding. JPEG is named after its origin, the Joint Photographers Experts Group. STABILITY - DSPGUIDE.COM Stability. The main limitation of digital filters carried out by convolution is execution time. It is possible to achieve nearly any filter response, provided you are willing to wait for the result. Recursive filters are just the opposite. They run like lightning; however, they are limited in performance. TELEVISION VIDEO SIGNALS In video jargon, the brightness is called the luminance signal, while the color is the chrominance signal. The chrominance signal is contained on a 3.58 MHz carrier wave added to the black and white video signal. Sound is added in this same way, on a 4.5 MHz carrier wave. The television receiver separates these three signals, processesthem
CHAPTER PROPERTIES OF CONVOLUTION Chapter 7- Properties of Convolution 127 FIGURE 7-3 Example of calculus-like operations. The signal in (b) is the first difference ofthe signal in (a).
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNALERRATAABOUT THE BOOKEIGHT GOOD REASONS FOR LEARNING DSPREVIEWSSTEVEN W. SMITH The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. CONVOLUTION VIA THE FREQUENCY DOMAIN Figure 9-8 provides an answer: transform the two signals into the frequency domain, multiply them, and then transform the result back into the time domain. This replaces one convolution with two DFTs, a multiplication, and an Inverse DFT. Even though the intermediate steps are very different, the output is identical to the standardconvolution
CIRCULAR BUFFERING
of samples, perform the algorithm, and output a group of samples. This is the world of Digital Signal Processors. Now look back at Fig. 28-2 and imagine that this is an FIR filter being implemented in real-time.To calculate the output sample, we must have access to a certain number of the most recent samples from the input. COMMON IMPULSE RESPONSES Common Impulse Responses. Delta Function. The simplest impulse response is nothing more that a delta function, as shown in Fig. 7-1a. That is, an impulse on the input produces an identical impulse on the output. This means that all signals are passed through the systemwithout change.
THE DIGITAL SIGNAL PROCESSOR MARKET The Digital Signal Processor Market. The DSP market is very large and growing rapidly. As shown in Fig. 28-14, it will be about 8-10 billion dollars/year at the turn of the century, and growing at a rate of 30-40% each year. This is being fueled by the incessant. demand for better and cheaper consumer products, such as: cellular telephones JPEG (TRANSFORM COMPRESSION) JPEG (Transform Compression) Many methods of lossy compression have been developed; however, a family of techniques called transform compression has proven the most valuable. The best example of transform compression is embodied in the popular JPEG standard of image encoding. JPEG is named after its origin, the Joint Photographers Experts Group. STABILITY - DSPGUIDE.COM Stability. The main limitation of digital filters carried out by convolution is execution time. It is possible to achieve nearly any filter response, provided you are willing to wait for the result. Recursive filters are just the opposite. They run like lightning; however, they are limited in performance. TELEVISION VIDEO SIGNALS In video jargon, the brightness is called the luminance signal, while the color is the chrominance signal. The chrominance signal is contained on a 3.58 MHz carrier wave added to the black and white video signal. Sound is added in this same way, on a 4.5 MHz carrier wave. The television receiver separates these three signals, processesthem
CHAPTER PROPERTIES OF CONVOLUTION Chapter 7- Properties of Convolution 127 FIGURE 7-3 Example of calculus-like operations. The signal in (b) is the first difference ofthe signal in (a).
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. DSP PROGRAMS AND FILES DSP Programs and Files. Courtesy of: The Scientist and Engineer's Guide to Digital Signal Processing. The following programs and files may be freely used for any noncommercial purpose.FILTER BASICS
The above equations use the base 10 logarithm; however, many computer languages only provide a function for the base e logarithm (the natural log, written log e x or ln x).The natural log can be use by modifying the above equations: dB = 4.342945 log e (P 2 /P 1) and dB = 8.685890 log e (A 2 /A 1).. Since decibels are a way of expressing the ratio between two signals, they are ideal for THE CHEBYSHEV AND BUTTERWORTH RESPONSES The Chebyshev response is an optimal trade-off between these two parameters. When the ripple is set to 0%, the filter is called a maximally flat or Butterworth filter (after S. Butterworth, a British engineer who described this response in 1930). A ripple of 0.5% is a often good choice for digital filters. This matches the typicalprecision and
THE DIGITAL SIGNAL PROCESSOR MARKET The Digital Signal Processor Market. The DSP market is very large and growing rapidly. As shown in Fig. 28-14, it will be about 8-10 billion dollars/year at the turn of the century, and growing at a rate of 30-40% each year. This is being fueled by the incessant. demand for better and cheaper consumer products, such as: cellular telephones ARCHITECTURE OF THE DIGITAL SIGNAL PROCESSOR Architecture of the Digital Signal Processor. One of the biggest bottlenecks in executing DSP algorithms is transferring information to and from memory. This includes data, such as samples from the input signal and the filter coefficients, as well as program instructions, the binary codes that go into the program sequencer.COMPLEX NUMBERS
Complex numbers are an extension of the ordinary numbers used in everyday math. They have the unique property of representing and manipulating two variables as a single quantity. This fits very naturally with Fourier analysis, where the frequency domain iscomposed of
COMMON DECOMPOSITIONS The even/odd decomposition, shown in Fig. 5-14, breaks a signal into two component signals, one having even symmetry and the other having odd symmetry. An N point signal is said to have even symmetry if it is a mirror image around point N/2. That is, sample x must equal x , sample x must equal x , etc. STRATEGY OF THE WINDOWED-SINC Figure 16-1 illustrates the idea behind the windowed-sinc filter. In (a), the frequency response of the ideal low-pass filter is shown. All frequencies below the cutoff frequency, f c, are passed with unity amplitude, while all higher frequencies are blocked.The passband is perfectly flat, the attenuation in the stopband is infinite, and the transition between the two is infinitesimally small. THREE EXAMPLES WHERE DSP SAVED MY BUTT! Three examples where DSP saved my butt! by Steve Smith Get Back - It's gonna blow! THE PROBLEM As shown below, the SECURE 1000 operates by passing an x-ray beam through various collimators, including a rotating chopper wheel containing several slits. As the chopper wheel rotates, a narrow beam of x-rays is formed that sweeps rapidly fromright-to-left.
THE LAPLACE TRANSFORM Chapter 32: The Laplace Transform. The two main techniques in signal processing, convolution and Fourier analysis, teach that a linear system can be completely understood from its THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNALERRATAABOUT THE BOOKEIGHT GOOD REASONS FOR LEARNING DSPREVIEWSSTEVEN W. SMITH The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. ARCHITECTURE OF THE DIGITAL SIGNAL PROCESSOR Architecture of the Digital Signal Processor. One of the biggest bottlenecks in executing DSP algorithms is transferring information to and from memory. This includes data, such as samples from the input signal and the filter coefficients, as well as program instructions, the binary codes that go into the program sequencer.FILTER BASICS
Filter Basics. Digital filters are a very important part of DSP. In fact, their extraordinary performance is one of the key reasons that DSP has become so popular. As mentioned in the introduction, filters have two uses: signal separation and signal restoration. Signal separation is needed when a signal has been contaminated withinterference
MATCH #1: ANALOG VS. DIGITAL FILTERS Fair is fair. Figure 21-1 shows the frequency and step responses for these two filters. Let's compare the two filters blow-by-blow. As shown in (a) and (b), the analog filter has a 6% ripple in the passband, while the digital filter is perfectly flat (within 0.02%). The analog designer might argue that the ripple can be selected in thedesign
CIRCULAR BUFFERING
of samples, perform the algorithm, and output a group of samples. This is the world of Digital Signal Processors. Now look back at Fig. 28-2 and imagine that this is an FIR filter being implemented in real-time.To calculate the output sample, we must have access to a certain number of the most recent samples from the input. STRATEGY OF THE WINDOWED-SINC Strategy of the Windowed-Sinc. Figure 16-1 illustrates the idea behind the windowed-sinc filter. In (a), the frequency response of the ideal low-pass filter is shown. All frequencies below the cutoff frequency, fc, are passed with unity amplitude, while all higher frequencies are blocked. The passband is perfectly flat, the attenuation in the FIXED VERSUS FLOATING POINT When this book was completed in 1999, fixed point DSPs sold for between $5 and $100, while floating point devices were in the range of $10 to $300. This difference in cost can be viewed as a measure of the relative complexity between the devices. If you want to find THE LAPLACE TRANSFORM Chapter 32: The Laplace Transform. The two main techniques in signal processing, convolution and Fourier analysis, teach that a linear system can be completely understood from its TELEVISION VIDEO SIGNALS In video jargon, the brightness is called the luminance signal, while the color is the chrominance signal. The chrominance signal is contained on a 3.58 MHz carrier wave added to the black and white video signal. Sound is added in this same way, on a 4.5 MHz carrier wave. The television receiver separates these three signals, processesthem
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNALERRATAABOUT THE BOOKEIGHT GOOD REASONS FOR LEARNING DSPREVIEWSSTEVEN W. SMITH The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. ARCHITECTURE OF THE DIGITAL SIGNAL PROCESSOR Architecture of the Digital Signal Processor. One of the biggest bottlenecks in executing DSP algorithms is transferring information to and from memory. This includes data, such as samples from the input signal and the filter coefficients, as well as program instructions, the binary codes that go into the program sequencer.FILTER BASICS
Filter Basics. Digital filters are a very important part of DSP. In fact, their extraordinary performance is one of the key reasons that DSP has become so popular. As mentioned in the introduction, filters have two uses: signal separation and signal restoration. Signal separation is needed when a signal has been contaminated withinterference
MATCH #1: ANALOG VS. DIGITAL FILTERS Fair is fair. Figure 21-1 shows the frequency and step responses for these two filters. Let's compare the two filters blow-by-blow. As shown in (a) and (b), the analog filter has a 6% ripple in the passband, while the digital filter is perfectly flat (within 0.02%). The analog designer might argue that the ripple can be selected in thedesign
CIRCULAR BUFFERING
of samples, perform the algorithm, and output a group of samples. This is the world of Digital Signal Processors. Now look back at Fig. 28-2 and imagine that this is an FIR filter being implemented in real-time.To calculate the output sample, we must have access to a certain number of the most recent samples from the input. STRATEGY OF THE WINDOWED-SINC Strategy of the Windowed-Sinc. Figure 16-1 illustrates the idea behind the windowed-sinc filter. In (a), the frequency response of the ideal low-pass filter is shown. All frequencies below the cutoff frequency, fc, are passed with unity amplitude, while all higher frequencies are blocked. The passband is perfectly flat, the attenuation in the FIXED VERSUS FLOATING POINT When this book was completed in 1999, fixed point DSPs sold for between $5 and $100, while floating point devices were in the range of $10 to $300. This difference in cost can be viewed as a measure of the relative complexity between the devices. If you want to find THE LAPLACE TRANSFORM Chapter 32: The Laplace Transform. The two main techniques in signal processing, convolution and Fourier analysis, teach that a linear system can be completely understood from its TELEVISION VIDEO SIGNALS In video jargon, the brightness is called the luminance signal, while the color is the chrominance signal. The chrominance signal is contained on a 3.58 MHz carrier wave added to the black and white video signal. Sound is added in this same way, on a 4.5 MHz carrier wave. The television receiver separates these three signals, processesthem
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNAL The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. CONVOLUTION VIA THE FREQUENCY DOMAIN Now back to frequency domain convolution. You may have noticed that we cheated slightly in Fig. 9-8. Remember, the convolution of an N point signal with an M point impulse response results in an N+M-1 point output signal.We cheated by making the last part of the input signal all zeros to allow this expansion to occur. Specifically, (a) contains 453 nonzero samples, and (b) contains 60 nonzero COMMON IMPULSE RESPONSES Common Impulse Responses. Delta Function. The simplest impulse response is nothing more that a delta function, as shown in Fig. 7-1a. That is, an impulse on the input produces an identical impulse on the output. This means that all signals are passed through the systemwithout change.
THE HISTOGRAM, PMF AND PDF The Histogram, Pmf and Pdf. Suppose we attach an 8 bit analog-to-digital converter to a computer, and acquire 256,000 samples of some signal. As an example, Fig. 2-4a shows 128 samples that might be a part of this data set. The value of each sample will be one of 256 possibilities, 0 through 255. The histogram displays the number ofsamples
FILTER COMPARISON
Chapter 21: Filter Comparison. Decisions, decisions, decisions! With all these filters to choose from, how do you know which to use? This chapter is a head-to-head competition between filters; we'll select champions from each side and let them fight it out.HUMAN HEARING
Human Hearing. The human ear is an exceedingly complex organ. To make matters even more difficult, the information from two ears is combined in a perplexing neural network, the human brain. Keep in mind that the following is only a brief overview; there are many subtle effects and poorly understood phenomena related to human hearing. THE SHARC EZ-KIT LITE The EZ-kit Lite gives you everything you need to learn about the SHARC DSP, including: hardware, software, and reference manuals. Figure 29-1 shows a block diagram of the hardware provided in the EZ-KIT Lite, based around the ADSP-21061 Digital Signal Processor. SINGLE BIT DATA CONVERSION capacitor is decreased when the circuit's output is a digital one, and increased when it is a digital zero.As the input signal increases and decreases in voltage, it tries to raise and lower the voltage on the capacitor. This change in voltage is detected by the comparator, resulting in the charge injectors producing a counteracting charge to keep the capacitor at zero volts. THREE EXAMPLES WHERE DSP SAVED MY BUTT! Three examples where DSP saved my butt! by Steve Smith Get Back - It's gonna blow! THE PROBLEM As shown below, the SECURE 1000 operates by passing an x-ray beam through various collimators, including a rotating chopper wheel containing several slits. As the chopper wheel rotates, a narrow beam of x-rays is formed that sweeps rapidly fromright-to-left.
CHAPTER PROPERTIES OF CONVOLUTION Chapter 7- Properties of Convolution 127 FIGURE 7-3 Example of calculus-like operations. The signal in (b) is the first difference ofthe signal in (a).
THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNALERRATAABOUT THE BOOKEIGHT GOOD REASONS FOR LEARNING DSPREVIEWSSTEVEN W. SMITH The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. ARCHITECTURE OF THE DIGITAL SIGNAL PROCESSORDIGITAL SIGNAL PROCESSOR PDFAPPLICATIONS OF DIGITAL SIGNAL PROCESSORSDIGITAL SIGNAL PROCESSORS DSPDIGITAL SIGNAL PROCESSORSBEST CAR AUDIO DSP PROCESSORDSP PROCESSORFILTER BASICS
Filter Basics. Digital filters are a very important part of DSP. In fact, their extraordinary performance is one of the key reasons that DSP has become so popular. As mentioned in the introduction, filters have two uses: signal separation and signal restoration. Signal separation is needed when a signal has been contaminated withinterference
MATCH #1: ANALOG VS. DIGITAL FILTERS Fair is fair. Figure 21-1 shows the frequency and step responses for these two filters. Let's compare the two filters blow-by-blow. As shown in (a) and (b), the analog filter has a 6% ripple in the passband, while the digital filter is perfectly flat (within 0.02%). The analog designer might argue that the ripple can be selected in thedesign
CIRCULAR BUFFERING
of samples, perform the algorithm, and output a group of samples. This is the world of Digital Signal Processors. Now look back at Fig. 28-2 and imagine that this is an FIR filter being implemented in real-time.To calculate the output sample, we must have access to a certain number of the most recent samples from the input. STRATEGY OF THE WINDOWED-SINC Strategy of the Windowed-Sinc. Figure 16-1 illustrates the idea behind the windowed-sinc filter. In (a), the frequency response of the ideal low-pass filter is shown. All frequencies below the cutoff frequency, fc, are passed with unity amplitude, while all higher frequencies are blocked. The passband is perfectly flat, the attenuation in the FIXED VERSUS FLOATING POINT When this book was completed in 1999, fixed point DSPs sold for between $5 and $100, while floating point devices were in the range of $10 to $300. This difference in cost can be viewed as a measure of the relative complexity between the devices. If you want to find THE LAPLACE TRANSFORM Chapter 32: The Laplace Transform. The two main techniques in signal processing, convolution and Fourier analysis, teach that a linear system can be completely understood from its TELEVISION VIDEO SIGNALS In video jargon, the brightness is called the luminance signal, while the color is the chrominance signal. The chrominance signal is contained on a 3.58 MHz carrier wave added to the black and white video signal. Sound is added in this same way, on a 4.5 MHz carrier wave. The television receiver separates these three signals, processesthem
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNALERRATAABOUT THE BOOKEIGHT GOOD REASONS FOR LEARNING DSPREVIEWSSTEVEN W. SMITH The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. ARCHITECTURE OF THE DIGITAL SIGNAL PROCESSORDIGITAL SIGNAL PROCESSOR PDFAPPLICATIONS OF DIGITAL SIGNAL PROCESSORSDIGITAL SIGNAL PROCESSORS DSPDIGITAL SIGNAL PROCESSORSBEST CAR AUDIO DSP PROCESSORDSP PROCESSORFILTER BASICS
Filter Basics. Digital filters are a very important part of DSP. In fact, their extraordinary performance is one of the key reasons that DSP has become so popular. As mentioned in the introduction, filters have two uses: signal separation and signal restoration. Signal separation is needed when a signal has been contaminated withinterference
MATCH #1: ANALOG VS. DIGITAL FILTERS Fair is fair. Figure 21-1 shows the frequency and step responses for these two filters. Let's compare the two filters blow-by-blow. As shown in (a) and (b), the analog filter has a 6% ripple in the passband, while the digital filter is perfectly flat (within 0.02%). The analog designer might argue that the ripple can be selected in thedesign
CIRCULAR BUFFERING
of samples, perform the algorithm, and output a group of samples. This is the world of Digital Signal Processors. Now look back at Fig. 28-2 and imagine that this is an FIR filter being implemented in real-time.To calculate the output sample, we must have access to a certain number of the most recent samples from the input. STRATEGY OF THE WINDOWED-SINC Strategy of the Windowed-Sinc. Figure 16-1 illustrates the idea behind the windowed-sinc filter. In (a), the frequency response of the ideal low-pass filter is shown. All frequencies below the cutoff frequency, fc, are passed with unity amplitude, while all higher frequencies are blocked. The passband is perfectly flat, the attenuation in the FIXED VERSUS FLOATING POINT When this book was completed in 1999, fixed point DSPs sold for between $5 and $100, while floating point devices were in the range of $10 to $300. This difference in cost can be viewed as a measure of the relative complexity between the devices. If you want to find THE LAPLACE TRANSFORM Chapter 32: The Laplace Transform. The two main techniques in signal processing, convolution and Fourier analysis, teach that a linear system can be completely understood from its TELEVISION VIDEO SIGNALS In video jargon, the brightness is called the luminance signal, while the color is the chrominance signal. The chrominance signal is contained on a 3.58 MHz carrier wave added to the black and white video signal. Sound is added in this same way, on a 4.5 MHz carrier wave. The television receiver separates these three signals, processesthem
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNAL The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. CONVOLUTION VIA THE FREQUENCY DOMAIN Now back to frequency domain convolution. You may have noticed that we cheated slightly in Fig. 9-8. Remember, the convolution of an N point signal with an M point impulse response results in an N+M-1 point output signal.We cheated by making the last part of the input signal all zeros to allow this expansion to occur. Specifically, (a) contains 453 nonzero samples, and (b) contains 60 nonzero COMMON IMPULSE RESPONSES Common Impulse Responses. Delta Function. The simplest impulse response is nothing more that a delta function, as shown in Fig. 7-1a. That is, an impulse on the input produces an identical impulse on the output. This means that all signals are passed through the systemwithout change.
THE HISTOGRAM, PMF AND PDF The Histogram, Pmf and Pdf. Suppose we attach an 8 bit analog-to-digital converter to a computer, and acquire 256,000 samples of some signal. As an example, Fig. 2-4a shows 128 samples that might be a part of this data set. The value of each sample will be one of 256 possibilities, 0 through 255. The histogram displays the number ofsamples
FILTER COMPARISON
Chapter 21: Filter Comparison. Decisions, decisions, decisions! With all these filters to choose from, how do you know which to use? This chapter is a head-to-head competition between filters; we'll select champions from each side and let them fight it out.HUMAN HEARING
Human Hearing. The human ear is an exceedingly complex organ. To make matters even more difficult, the information from two ears is combined in a perplexing neural network, the human brain. Keep in mind that the following is only a brief overview; there are many subtle effects and poorly understood phenomena related to human hearing. THE SHARC EZ-KIT LITE The EZ-kit Lite gives you everything you need to learn about the SHARC DSP, including: hardware, software, and reference manuals. Figure 29-1 shows a block diagram of the hardware provided in the EZ-KIT Lite, based around the ADSP-21061 Digital Signal Processor. SINGLE BIT DATA CONVERSION capacitor is decreased when the circuit's output is a digital one, and increased when it is a digital zero.As the input signal increases and decreases in voltage, it tries to raise and lower the voltage on the capacitor. This change in voltage is detected by the comparator, resulting in the charge injectors producing a counteracting charge to keep the capacitor at zero volts. THREE EXAMPLES WHERE DSP SAVED MY BUTT! Three examples where DSP saved my butt! by Steve Smith Get Back - It's gonna blow! THE PROBLEM As shown below, the SECURE 1000 operates by passing an x-ray beam through various collimators, including a rotating chopper wheel containing several slits. As the chopper wheel rotates, a narrow beam of x-rays is formed that sweeps rapidly fromright-to-left.
CHAPTER PROPERTIES OF CONVOLUTION Chapter 7- Properties of Convolution 127 FIGURE 7-3 Example of calculus-like operations. The signal in (b) is the first difference ofthe signal in (a).
THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNALERRATAABOUT THE BOOKEIGHT GOOD REASONS FOR LEARNING DSPREVIEWSSTEVEN W. SMITH The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. ARCHITECTURE OF THE DIGITAL SIGNAL PROCESSORDIGITAL SIGNAL PROCESSOR PDFAPPLICATIONS OF DIGITAL SIGNAL PROCESSORSDIGITAL SIGNAL PROCESSORS DSPDIGITAL SIGNAL PROCESSORSBEST CAR AUDIO DSP PROCESSORDSP PROCESSORFILTER BASICS
Filter Basics. Digital filters are a very important part of DSP. In fact, their extraordinary performance is one of the key reasons that DSP has become so popular. As mentioned in the introduction, filters have two uses: signal separation and signal restoration. Signal separation is needed when a signal has been contaminated withinterference
MATCH #1: ANALOG VS. DIGITAL FILTERS Fair is fair. Figure 21-1 shows the frequency and step responses for these two filters. Let's compare the two filters blow-by-blow. As shown in (a) and (b), the analog filter has a 6% ripple in the passband, while the digital filter is perfectly flat (within 0.02%). The analog designer might argue that the ripple can be selected in thedesign
CIRCULAR BUFFERING
of samples, perform the algorithm, and output a group of samples. This is the world of Digital Signal Processors. Now look back at Fig. 28-2 and imagine that this is an FIR filter being implemented in real-time.To calculate the output sample, we must have access to a certain number of the most recent samples from the input. STRATEGY OF THE WINDOWED-SINC Strategy of the Windowed-Sinc. Figure 16-1 illustrates the idea behind the windowed-sinc filter. In (a), the frequency response of the ideal low-pass filter is shown. All frequencies below the cutoff frequency, fc, are passed with unity amplitude, while all higher frequencies are blocked. The passband is perfectly flat, the attenuation in the FIXED VERSUS FLOATING POINT When this book was completed in 1999, fixed point DSPs sold for between $5 and $100, while floating point devices were in the range of $10 to $300. This difference in cost can be viewed as a measure of the relative complexity between the devices. If you want to find THE LAPLACE TRANSFORM Chapter 32: The Laplace Transform. The two main techniques in signal processing, convolution and Fourier analysis, teach that a linear system can be completely understood from its TELEVISION VIDEO SIGNALS In video jargon, the brightness is called the luminance signal, while the color is the chrominance signal. The chrominance signal is contained on a 3.58 MHz carrier wave added to the black and white video signal. Sound is added in this same way, on a 4.5 MHz carrier wave. The television receiver separates these three signals, processesthem
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNALERRATAABOUT THE BOOKEIGHT GOOD REASONS FOR LEARNING DSPREVIEWSSTEVEN W. SMITH The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. ARCHITECTURE OF THE DIGITAL SIGNAL PROCESSORDIGITAL SIGNAL PROCESSOR PDFAPPLICATIONS OF DIGITAL SIGNAL PROCESSORSDIGITAL SIGNAL PROCESSORS DSPDIGITAL SIGNAL PROCESSORSBEST CAR AUDIO DSP PROCESSORDSP PROCESSORFILTER BASICS
Filter Basics. Digital filters are a very important part of DSP. In fact, their extraordinary performance is one of the key reasons that DSP has become so popular. As mentioned in the introduction, filters have two uses: signal separation and signal restoration. Signal separation is needed when a signal has been contaminated withinterference
MATCH #1: ANALOG VS. DIGITAL FILTERS Fair is fair. Figure 21-1 shows the frequency and step responses for these two filters. Let's compare the two filters blow-by-blow. As shown in (a) and (b), the analog filter has a 6% ripple in the passband, while the digital filter is perfectly flat (within 0.02%). The analog designer might argue that the ripple can be selected in thedesign
CIRCULAR BUFFERING
of samples, perform the algorithm, and output a group of samples. This is the world of Digital Signal Processors. Now look back at Fig. 28-2 and imagine that this is an FIR filter being implemented in real-time.To calculate the output sample, we must have access to a certain number of the most recent samples from the input. STRATEGY OF THE WINDOWED-SINC Strategy of the Windowed-Sinc. Figure 16-1 illustrates the idea behind the windowed-sinc filter. In (a), the frequency response of the ideal low-pass filter is shown. All frequencies below the cutoff frequency, fc, are passed with unity amplitude, while all higher frequencies are blocked. The passband is perfectly flat, the attenuation in the FIXED VERSUS FLOATING POINT When this book was completed in 1999, fixed point DSPs sold for between $5 and $100, while floating point devices were in the range of $10 to $300. This difference in cost can be viewed as a measure of the relative complexity between the devices. If you want to find THE LAPLACE TRANSFORM Chapter 32: The Laplace Transform. The two main techniques in signal processing, convolution and Fourier analysis, teach that a linear system can be completely understood from its TELEVISION VIDEO SIGNALS In video jargon, the brightness is called the luminance signal, while the color is the chrominance signal. The chrominance signal is contained on a 3.58 MHz carrier wave added to the black and white video signal. Sound is added in this same way, on a 4.5 MHz carrier wave. The television receiver separates these three signals, processesthem
STEVEN W. SMITH
Steven W. Smith, Ph.D.PresidentTek84 Engineering Group10907 Technology PlaceSan Diego, CA 92127. Steve Smith specializes in developing novel imaging systems for medicine, security, and industrial applications. Two of his major projects have been the SECURE 1000 and SentryScope. THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNAL The Scientist and Engineer's Guide toDigital Signal ProcessingBy Steven W. Smith, Ph.D. The Scientist and Engineer's Guide to. Digital Signal Processing. By Steven W. Smith, Ph.D. CONVOLUTION VIA THE FREQUENCY DOMAIN Now back to frequency domain convolution. You may have noticed that we cheated slightly in Fig. 9-8. Remember, the convolution of an N point signal with an M point impulse response results in an N+M-1 point output signal.We cheated by making the last part of the input signal all zeros to allow this expansion to occur. Specifically, (a) contains 453 nonzero samples, and (b) contains 60 nonzero COMMON IMPULSE RESPONSES Common Impulse Responses. Delta Function. The simplest impulse response is nothing more that a delta function, as shown in Fig. 7-1a. That is, an impulse on the input produces an identical impulse on the output. This means that all signals are passed through the systemwithout change.
THE HISTOGRAM, PMF AND PDF The Histogram, Pmf and Pdf. Suppose we attach an 8 bit analog-to-digital converter to a computer, and acquire 256,000 samples of some signal. As an example, Fig. 2-4a shows 128 samples that might be a part of this data set. The value of each sample will be one of 256 possibilities, 0 through 255. The histogram displays the number ofsamples
FILTER COMPARISON
Chapter 21: Filter Comparison. Decisions, decisions, decisions! With all these filters to choose from, how do you know which to use? This chapter is a head-to-head competition between filters; we'll select champions from each side and let them fight it out.HUMAN HEARING
Human Hearing. The human ear is an exceedingly complex organ. To make matters even more difficult, the information from two ears is combined in a perplexing neural network, the human brain. Keep in mind that the following is only a brief overview; there are many subtle effects and poorly understood phenomena related to human hearing. THE SHARC EZ-KIT LITE The EZ-kit Lite gives you everything you need to learn about the SHARC DSP, including: hardware, software, and reference manuals. Figure 29-1 shows a block diagram of the hardware provided in the EZ-KIT Lite, based around the ADSP-21061 Digital Signal Processor. SINGLE BIT DATA CONVERSION capacitor is decreased when the circuit's output is a digital one, and increased when it is a digital zero.As the input signal increases and decreases in voltage, it tries to raise and lower the voltage on the capacitor. This change in voltage is detected by the comparator, resulting in the charge injectors producing a counteracting charge to keep the capacitor at zero volts. THREE EXAMPLES WHERE DSP SAVED MY BUTT! Three examples where DSP saved my butt! by Steve Smith Get Back - It's gonna blow! THE PROBLEM As shown below, the SECURE 1000 operates by passing an x-ray beam through various collimators, including a rotating chopper wheel containing several slits. As the chopper wheel rotates, a narrow beam of x-rays is formed that sweeps rapidly fromright-to-left.
CHAPTER PROPERTIES OF CONVOLUTION Chapter 7- Properties of Convolution 127 FIGURE 7-3 Example of calculus-like operations. The signal in (b) is the first difference ofthe signal in (a).
THE SCIENTIST AND ENGINEER'S GUIDE TO DIGITAL SIGNAL PROCESSING BY STEVEN W. SMITH, PH.D.* Home
* The Book by Chapters* About the Book
* Copyright and permissible use* What is DSP?
* 8 good reasons for learning DSP * Comments by reviewers* Errata
* Free Software and Teaching Aids * Differences Between Editions* Steven W. Smith
* Blog
* Contact
Yes, It's true - You can browse and/or download the entire bookwithout charge
» Browse and/or download chapters from the book » Copyright and permissible use HOW TO ORDER YOUR OWN HARDCOVER COPY Wouldn't you rather have a bound book instead of 640 loose pages? Your laser printer will thank you! ORDER FROM AMAZON.COM.
BOOK SEARCH
RECOMMENDED DSP SITESDSPRelated.com
640 PAGES, HARDCOVER Over 500 graphs and illustrationsCLEAR EXPLANATIONS
Very readable - low math - many examples ALL THE CLASSIC DSP TECHNIQUES Convolution, Recursion, Fourier Analysis... EASY TO USE DIGITAL FILTERS Simple to design; incredible performanceNEW APPLICATIONS
Topics usually reserved for specialized books: audio and image processing, neural networks, data compression, and more! FOR STUDENTS AND PROFESSIONALS Written for a wide range of fields: physics, bioengineering, geology, oceanography, mechanical and electrical engineeringABOUT THE BOOK
* What is DSP?
* Why you need this book (8 good reasons for learning DSP)
* Comments by reviewers* Errata
* Free software and teaching aids * What is the difference between the book editions?
_(Titles, hard cover, paperback, ISBN numbers)_ ABOUT THE AUTHOR AND HIS WORK * Steve Smith's home page * Steve Smith's research and development group: * Tek84 Engineering Group Home | The Book by Chapters| About the Book
| Steven W. Smith
| Blog
| Contact
Copyright © 1997-2011 by California Technical PublishingDetails
Copyright © 2024 ArchiveBay.com. All rights reserved. Terms of Use | Privacy Policy | DMCA | 2021 | Feedback | Advertising | RSS 2.0