离散时间信号处理(第三版)(英文版)

.2.9.2 time shifting and frequency shifting theorem
2.9.3 time reversal theorem
2.9.4 differentiation in frequency theorem
2.9.5 parseval\'s theorem
2.9.6 the convolution theorem
2.9.7 the modulation or windowing theorem
2.10 discrete-time random signals
2.11 summary
problems
the z-transform
3.0 introduction
3.1 z-transform
3.2 properties of the roc for the z-transform
3.3 the inverse z-transform
3.3.1 inspection method
3.3.2 partial fraction expansion
3.3.3 power series expansion
3.4 z-transform properties
3.4.1 linearity
3.4.2 time shifting
3.4.3 multiplication by an exponential sequence
3.4.4 differentiation of x（z）" ~
3.4.5 conjugation of a complex sequence
3.4.6 time reversal
3.4.7 convolution of sequences
3.4.8 summary of some z-transform properties
3.5 z-transforms and lti systems
3.6 the unilateral z-transform
3.7 summary
problems
sampling of continuous-time signals
4.0 introduction
4.1 periodic sampling
4.2 frequency-domain representation of sampling .
4.3 reconstruction of a bandlimited signal from its samples
4.4 discrete-time processing of continuous-time signals
4.4.1 discrete-time lti processing of continuous-time signals . .
4.4.2 impulse invariance
4.5 continuous-time processing of discrete-time signals
4.6 changing the sampling rate using discrete-time processing
4.6.1 sampling rate reduction by an integer factor
4.6.2 increasing the sampling rate by an integer factor
4.6.3 simple and practical interpolation filters
4.6.4 changing the sampling rate by a noninteger factor
4.7 multirate signal processing
4.7.1 interchange of filtering with compressor/expander
4.7.2 multistage decimation and interpolation
4.7.3 polyphase decompositions
4.7.4 polyphase implementation of decimation filters
4.7.5 polyphase implementation of interpolation filters
4.7.6 multirate filter banks
4.8 digital processing of analog signals
4.8.1 prefiltering to avoid aliasing
4.8.2 a/d conversion
4.8.3 analysis of quantization errors
4.8.4 d/a conversion
4.9 oversampling and noise shaping in a/d and d/a conversion
4.9.1 oversampled a/d conversion with direct quantization
4.9.2 oversampled a/d conversion with noise shaping
4.9.3 oversampling and noise shaping in d/a conversion
4.10 summary
problems
transform analysis of linear time-invariant systems
5.0 introduction
5.1 the frequency response of lti systems
5.1.1 frequency response phase and group delay
5.1.2 illustration of effects of group delay and attenuation
5.2 system functions——linear constant-coefficient difference equations
5.2.1 stability and causality
5.2.2 inverse systems
5.2.3 impulse response for rational system functions
5.3 frequency response for rational system functions
5.3.1 frequency response of lst-order systems
5.3.2 examples with multiple poles and zeros
5.4 relationship between magnitude and phase
5.5 all-pass systems
5.6 minimum-phase systems
5.6.1 minimum-phase and all-pass decomposition
5.6.2 frequency-response compensation of non-minimum-phase systems
5.6.3 properties of minimum-phase systems
5.7 linear systems with generalized linear phase
5.7.1 systems with linear phase
5.7.2 generalized linear phase
5.7.3 causal generalized linear-phase systems
5.7.4 relation of fir linear-phase systems to minimum-phase systems
5.8 summary
problems
structures for discrete-time systems
6.0 introduction
6.1 block diagram representation of linear constant-coefficient difference equations
6.2 signal flow graph representation
6.3 basic structures for iir systems
6.3.1 direct forms
6.3.2 cascade form
6.3.3 parallel form
6.3.4 feedback in iir systems
6.4 transposed forms
6.5 basic network structures for fir systems
6.5.1 direct form
6.5.2 cascade form
6.5.3 structures for linear-phase fir systems
6.6 lattice filters
6.6.1 fir lattice filters
6.6.2 all-pole lattice structure
6.6.3 generalization of lattice systems
6.7 overview of finite-precision numerical effects
6.7.1 number representations
6.7.2 quantization in implementing systems
6.8 the effects of coefficient quantization
6.8.1 effects of coefficient quantization in iir systems
6.8.2 example of coefficient quantization in an elliptic filter
6.8.3 poles of quantized 2hal-order sections
6.8.4 effects of coefficient quantization in fir systems
6.8.5 example of quantization of an optimum fir filter
6.8.6 maintaining linear phase
6.9 effects of round-off noise in digital filters
6.9.1 analysis of the direct form iir structures
6.9.2 scaling in fixed-point implementations of iir systems
6.9.3 example of analysis of a cascade iir structure
6.9.4 analysis of direct-form fir systems
6.9.5 floating-point realizations of discrete-time systems
6.10 zero4nput limit cycles in fixed-point realizations of iir digital filters
6.10.1 limit cycles owing to round-off and truncation
6.10.2 limit cycles owing to overflow
6.10.3 avoiding limit cycles
6.11 summary
problems
filter design techniques
7.0 introduction
7.1 filter specifications
……
the discrete fourier tranaform
computation of the discrete fourier transform
fourier analysis of signals using the discrete fourier transform
parametric signal modeling
discrete hilbert transforms