Applied Digital Signal Processing: Theory and Practice
Cambridge University Press, Nov 21, 2011 - Technology & Engineering - 1008 pages
Master the basic concepts and methodologies of digital signal processing with this systematic introduction, without the need for an extensive mathematical background. The authors lead the reader through the fundamental mathematical principles underlying the operation of key signal processing techniques, providing simple arguments and cases rather than detailed general proofs. Coverage of practical implementation, discussion of the limitations of particular methods and plentiful MATLAB illustrations allow readers to better connect theory and practice. A focus on algorithms that are of theoretical importance or useful in real-world applications ensures that students cover material relevant to engineering practice, and equips students and practitioners alike with the basic principles necessary to apply DSP techniques to a variety of applications. Chapters include worked examples, problems and computer experiments, helping students to absorb the material they have just read. Lecture slides for all figures and solutions to the numerous problems are available to instructors.
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10 Design of FIR filters
11 Design of IIR filters
12 Multirate signal processing
13 Random signals
14 Random signal processing
15 Finite wordlength effects
9 Structures for discretetime systems
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aliasing allpass analog approximation attenuation bandpass bits cascade form causal Chebyshev coefficients complex exponentials Compute and plot continuous-time signal convolution decimation Determine difference equation digital filter direct form discrete-time signal discrete-time system DTFT equiripple error estimator Example FFT algorithm ﬁlter filter bank filter design finite FIR filter FIR system Fourier transform frequency response given group-delay highpass ideal implementation impulse response impulse response h[n input signal integer interpolation Kaiser window linear linear-phase lowpass filter LTI system magnitude response MATLAB MATLAB function matrix N-point noise obtain operation output passband periodic periodogram phase response pole-zero poles polynomial properties provides quantization radians random variables representation resulting sampling rate second-order sections sequence x[n shown in Figure shows signal processing signal x[n sinusoidal specifications spectral spectrum SQNR stopband structure system function H(z transition band Tutorial Problem unit circle values variance vector window xc(t z-transform zero