Author:
Mitra, Sanjit Kumar.
Edition Statement:4th ed.
Imprint:New York, NY : McGraw-Hill, c2011.
Descriptionxx, 940 p. : ill. ; 25 cm. + 1 CD-ROM (4 3/4 in.)
Note:1. Signals and signal processing -- 1.1. Characterization and classification of signals -- 1.2. Typical signal processing operations -- 1.3. Examples of typical signals -- 1.4. Typical signal processing applications -- 1.5. Why digital signal processing? -- 2. Discrete-time signals in the time domain -- 2.1. Time-domain representation -- 2.2. Operations on sequences -- 2.3. Operations on finite-length sequences -- 2.4. Typical sequences and sequence representation -- 2.5. The sampling process -- 2.6. Correlation of signals -- 2.7. Random signals -- 2.8. Summary -- 2.9. Problems -- 2.10. Matlab exercises -- 3. Discrete-time signals in the frequency domain -- 3.1. The continuous-time Fourier transform -- 3.2. The discrete-time Fourier transform -- 3.3. Discrete-time Fourier transform theorems -- 3.4. Energy density spectrum of a discrete-time sequence -- 3.5. Band-limited discrete-time signals -- 3.6. DTFT computation using Matlab -- 3.7. The unwrapped phase function -- 3.8. Digital processing of continuous-time signals -- 3.9. Sampling of bandpass signals -- 3.10. Effect of sample-and-hold operation -- 3.11. Summary -- 3.12. Problems -- 3.13. Matlab exercises -- 4. Discrete-time systems -- 4.1. Discrete-time system examples -- 4.2. Classification of discrete-time systems -- 4.3. Impulse and step responses -- 4.4. Time-domain characterization of LTI discrete-time systems -- 4.5. Simple interconnection schemes -- 4.6. Finite-dimensional LTI discrete-time systems -- 4.7. Classification of LTI discrete-time systems -- 4.8. Frequency-domain representations of LTI discrete-time systems -- 4.9. Phase and group delays -- 4.10. Summary -- 4.11. Problems -- 4.12. Matlab exercises -- 5. Finite-length discrete transforms -- 5.1. Orthogonal transforms -- 5.2. The discrete Fourier transform -- 5.3. Relation between the DTFT and the DFT and their inverses. -- 5.4. Circular convolution -- 5.5. Classifications of finite-length sequences -- 5.6. DFT symmetry relations -- 5.7. Discrete Fourier transform theorems -- 5.8. Fourier-domain filtering -- 5.9. Computation of the DFT of real sequences -- 5.10. Linear convolution using the DFT -- 5.11. Short-time Fourier transform -- 5.12. Discrete cosine transform -- 5.13. The Haar transform -- 5.14. Energy compaction properties -- 5.15. Summary -- 5.16. Problems -- 5.17. Matlab exercises -- 6. z-transform -- 6.1. Definition -- 6.2. Rational z-transforms -- 6.3. Region of convergence of a rational z-transform -- 6.4. The inverse z-transform -- 6.5. z-transform theorems -- 6.6. Computation of the convolution sum of finite-length sequences -- 6.7. The transfer function -- 6.8. Summary -- 6.9. Problems -- 6.10. Matlab exercises -- 7. LTI discrete-time systems in the transform domain -- 7.1. Transfer function classification based on magnitude characteristics -- 7.2. Transfer function classification based on phase characteristics -- 7.3. Types of linear-phase FIR transfer functions -- 7.4. Simple digital filters -- 7.5. Complementary transfer functions -- 7.6. Inverse systems -- 7.7. System identification -- 7.8. Digital two-pairs -- 7.9. Algebraic stability test -- 7.10. Summary -- 7.11. Problems -- 7.12. Matlab exercises -- 8. Digital filter structures -- 8.1. Block diagram representation -- 8.2. Equivalent structures -- 8.3. Basic FIR digital filter structures -- 8.4. Basic IIR digital filter structures -- 8.5. Realization of basic structures using Matlab -- 8.6. Allpass filters -- 8.7. Parametrically tunable low-order IIR digital filter pairs -- 8.8. IIR tapped cascaded lattice structures -- 8.9. FIR cascaded lattice structures -- 8.10. Parallel allpass realization of IIR transfer functions -- 8.11. Tunable high-order digital filters. -- 8.12. Computational complexity of digital filter structures -- 8.13. Summary -- 8.14. Problems -- 8.15. Matlab exercises -- 9. IIR digital filter design -- 9.1. Preliminary considerations -- 9.2. Bilinear transformation method of IIR filter design -- 9.3. Design of lowpass IIR digital filters -- 9.4. Design of highpass, bandpass, and bandstop IIR digital filters -- 9.5. Spectral transformations of IIR filters -- 9.6. IIR digital filter design using Matlab -- 9.7. Computer-aided design of IIR digital filters -- 9.8. Summary -- 9.9. Problems -- 9.10 ; Matlab exercises -- 10. FIR digital filter design -- 10.1. Preliminary considerations -- 10.2. FIR filter design based on windowed Fourier series -- 10.3. Computer-aided design of equiripple linear-phase FIR filters -- 10.4. Design of minimum-phase FIR filters -- 10.5. FIR digital filter design using Matlab -- 10.6. Design of computationally efficient FIR digital filters -- 10.7. Summary -- 10.8. Problems -- 10.9. Matlab exercises -- 11. DSP algorithm implementation -- 11.1. Basic issues -- 11.2. Structure simulation and verification using Matlab -- 11.3. Computation of the discrete Fourier transform -- 11.4. Fast DFT algorithms based on index mapping -- 11.5. DFT and IDFT computation using Matlab -- 11.6. Sliding discrete Fourier transform -- 11.7. DFT computation over a narrow frequency band -- 11.8. Number representation -- 11.9. Handling of overflow -- 11.10. Summary -- 11.11. Problems -- 11.12. Matlab exercises -- 12. Analysis of finite wordlength effects -- 12.1. The quantization process and errors -- 12.2. Quantization of fixed-point numbers -- 12.3. Quantization of floating-point numbers -- 12.4. Analysis of coefficient quantization effects -- 12.5. A/D conversion noise analysis -- 12.6. Analysis of arithmetic round-off errors -- 12.7. Dynamic range scaling -- 12.8. Signal-to-noise ratio in low-order IIR filters. -- 12.9. Low-sensitivity digital filters -- 12.10. Reduction of product round-off noise using error feedback -- 12.11. Limit cycles in IIR digital filters -- 12.12. Round-off errors in FFT algorithms -- 12.13. Summary -- 12.14. Problems -- 12.15. Matlab exercises -- 13. Multirate digital signal processing fundamentals -- 13.1. The basic sampling rate alteration devices -- 13.2. Multirate structures for sampling rate conversion -- 13.3. Multistage design of decimator and interpolator -- 13.4. The polyphase decomposition -- 13.5. Arbitrary-rate sampling rate converter -- 13.6. Nyquist filters -- 13.7. CIC decimators and interpolators -- 13.8. Summary -- 13.9. Problems -- 13.10. Matlab exercises -- 14. Multirate filter banks and wavelets -- 14.1. Digital filter banks -- 14.2. Two-channel quadrature-mirror filter bank -- 14.3. Perfect reconstruction two-channel FIR filter banks -- 14.4. L-channel QMF banks -- 14.5. Multilevel filter banks -- 14.6. Discrete wavelet transform -- 14.7. Summary -- 14.8. Problems -- 14.9. Matlab exercises -- A. Analog lowpass filter design -- A.1. Analog filter specifications -- A.2. Butterworth approximation -- A.3. Chebyshev approximation -- A.4. Elliptic approximation -- A.5. Linear-phase approximation -- A.6. Analog filter design using Matlab -- A.7. Analog lowpass filter design examples -- A.8. A comparison of the filter types -- A.9. Anti-aliasing filter design -- A.10. Reconstruction filter design -- B. Design of analog highpass, bandpass, and bandstop filters -- B.1. Analog highpass filter design -- B.2. Analog bandpass filter design -- B.3. Analog bandstop filter design -- C. Discrete-time random signals -- C.1. Statistical properties of a random variable -- C.2. Statistical properties of a random signal -- C.3. Wide-sense stationary random signal -- C.4. Concept of power in a random signal -- C.5. Ergodic signal. -- C.6. Transform-domain representations of random signals -- C.7. White noise -- C.8. Discrete-time processing of random signals.
Bibliography Note:Includes bibliographical references (p. 907-925) index.
