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Digital Signal Processing with Examples in MATLAB®, Second Edition [Kõva köide]

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(Sandia National Laboratories, Albuquerque, New Mexico, USA), (Sandia National Laboratories, Albuquerque, New Mexico, USA), (Los Alamos National Laboratory, New Mexico, USA)
  • Formaat: Hardback, 360 pages, kõrgus x laius: 235x156 mm, kaal: 612 g, 518 equations; 17 Tables, black and white; 185 Illustrations, black and white, Contains 9 hardbacks
  • Sari: Electrical Engineering & Applied Signal Processing Series
  • Ilmumisaeg: 28-Aug-2002
  • Kirjastus: CRC Press Inc
  • ISBN-10: 0849310911
  • ISBN-13: 9780849310911
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Digital Signal Processing with Examples in MATLAB®, Second EditionSuurem pilt
  • Formaat: Hardback, 360 pages, kõrgus x laius: 235x156 mm, kaal: 612 g, 518 equations; 17 Tables, black and white; 185 Illustrations, black and white, Contains 9 hardbacks
  • Sari: Electrical Engineering & Applied Signal Processing Series
  • Ilmumisaeg: 28-Aug-2002
  • Kirjastus: CRC Press Inc
  • ISBN-10: 0849310911
  • ISBN-13: 9780849310911
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780849310911.html
Märksõnad:
In a field as rapidly expanding as digital signal processing, even the topics relevant to the basics change over time both in their nature and their relative importance. It is important, therefore, to have an up-to-date text that not only covers the fundamentals, but that also follows a logical development that leaves no gaps readers must somehow bridge by themselves.

Digital Signal Processing with Examples in MATLAB® is just such a text. The presentation does not focus on DSP in isolation, but relates it to continuous signal processing and treats digital signals as samples of physical phenomena. The author also takes care to introduce important topics not usually addressed in signal processing texts, including the discrete cosine and wavelet transforms, multirate signal processing, signal coding and compression, least squares systems design, and adaptive signal processing. He also uses the industry-standard software MATLAB to provide examples of signal processing, system design, spectral analysis, filtering, coding and compression, and exercise solutions. All of the examples and functions used in the text are available online at www.crcpress.com.

Designed for a one-semester upper-level course but also ideal for self-study and reference, Digital Signal Processing with Examples in MATLAB is complete, self-contained, and rigorous. For basic DSP, it is quite simply the only book you need.
Introduction
1(18)
Digital Signal Processing
1(1)
How to Read this Text
2(1)
Introduction to Matlab
2(1)
Signals, Vectors, and Arrays
3(2)
Review of Vector and Matrix Algebra Using Matlab Notation
5(7)
Geometric Series and Other Formulas
12(2)
Matlab Functions in DSP
14(1)
The
Chapters Ahead
15(4)
References
16(3)
Least Squares, Orthogonality, and the Fourier Series
19(20)
Introduction
19(1)
Least Squares
19(5)
Orthogonality
24(2)
The Discrete Fourier Series
26(7)
Exercises
33(6)
References
37(2)
Correlation, Fourier Spectra, and the Sampling Theorem
39(32)
Introduction
39(1)
Correlation
40(2)
The Discrete Fourier Transform (DFT)
42(1)
Redundancy in the DFT
43(2)
The FFT algorithm
45(3)
Amplitude and Phase Spectra
48(3)
The Inverse DFT
51(1)
Properties of the DFT
52(6)
Continuous Transforms
58(2)
The Sampling Theorem
60(2)
Waveform Reconstruction and Aliasing
62(4)
Exercises
66(5)
References
69(2)
Linear Systems and Transfer Functions
71(40)
Continuous and Discrete Linear Systems
71(1)
Properties of Discrete Linear Systems
71(3)
Discrete Convolution
74(1)
The z-Transform and Linear Transfer Functions
75(2)
Poles and Zeros
77(4)
Transient Response and Stability
81(2)
System Response via the Inverse z-Transform
83(1)
Cascade, Parallel, and Feedback Structures
84(3)
Direct Algorithms
87(2)
State-Space Algorithms
89(2)
Lattice Algorithms and Structures
91(8)
FFT Algorithms
99(4)
Discrete Linear Systems and Digital Filters
103(2)
Exercises
105(6)
References
108(3)
FIR Filter Design
111(24)
Introduction
111(1)
An Ideal Lowpass Filter
112(1)
The Realizable Version
113(3)
Improving an FIR Filter with Window Functions
116(5)
Highpass, Bandpass, and Bandstop Filters
121(4)
A Complete FIR Filtering Example
125(1)
Other Types of FIR Filters
126(4)
Exercises
130(5)
References
133(2)
IIR Filter Design
135(32)
Introduction
135(1)
Linear Phase
136(1)
Butterworth Filters
137(4)
Chebyshev Filters
141(6)
Frequency Translations
147(2)
The Bilinear Transformation
149(4)
IIR Digital Filters
153(4)
Other Types of IIR Filters
157(5)
Exercises
162(5)
References
165(2)
Random Signals and Spectral Estimation
167(32)
Introduction
167(1)
Amplitude Distributions
168(3)
Uniform, Gaussian, and Other Distributions
171(6)
Power and Power Density Spectra
177(4)
Properties of the Power Spectrum
181(3)
Power Spectral Estimation
184(4)
Data Windows in Spectral Estimation
188(2)
The Cross-Power Spectrum
190(3)
Algorithms
193(1)
Exercises
194(5)
References
197(2)
Least-Squares System Design
199(42)
Introduction
199(1)
Applications of Least-Squares Design
200(3)
System Design via the Mean-Squared Error
203(4)
Design Example
207(3)
Least-Squares Design with Finite Signal Vectors
210(2)
Correlation and Covariance Computation
212(3)
Channel Equalization
215(2)
System Identification
217(3)
Interference Canceling
220(3)
Linear Prediction and Recovery
223(5)
Effects of Independent Broadband Noise
228(2)
Exercises
230(11)
References
238(3)
Adaptive Signal Processing
241(36)
Introduction
241(1)
The Mean-Squared Error Performance Surface
242(2)
Searching the Performance Surface
244(5)
Steepest Descent and the LMS Algorithm
249(6)
LMS Examples
255(3)
Direct Descent and the RLS Algorithm
258(5)
Measures of Adaptive System Performance
263(4)
Other Adaptive Structures and Algorithms
267(1)
Exercises
268(9)
References
273(4)
Signal Information, Coding, and Compression
277(42)
Introduction
277(1)
Measuring Information
278(2)
Two Ways to Compress Signals
280(2)
Entropy Coding
282(9)
Transform Coding and the Discrete Cosine Transform
291(7)
Multirate Signal Decomposition and Subband Coding
298(10)
Time-Frequency Analysis and Wavelet Transforms
308(4)
Exercises
312(7)
References
317(2)
Index 319