Fundamentals of Digital Signal Processing Using MATLAB (with CD-ROM)

Robert J. Schilling is Professor Emeritus of Electrical and Computer Engineering at Clarkson University. Dr. Schilling's teaching interests include digital signal processing, control systems, robotics, nonlinear systems, computer graphics, and C++ and MATLAB� programming. His research interests encompass adaptive signal processing, nonlinear system identification, active noise control, and control of robotic manipulators. Bio: Sandra L. Harris is Associate Professor Emeritus of Chemical Engineering at Clarkson University. Dr. Harris's teaching interests include process control, thermodynamics, and biochemical engineering. Her research interests center around periodic processing, control of systems having varying dead times, and the generation of input signals for efficient process identification.

1. Signal Processing
Motivation / Signals and Systems / Signal Sampling / Signal Reconstruction / Prefilters and Postfilters / Conversion Circuits / The FDSP Toolbox / Software Applications / Chapter Summary / Problems
2. Discrete-Time System Analysis
Motivation / Z-Transform Pairs / Z-Transform Properties / Inverse Z-Transform / Transfer Functions / Signal Flow Graphs / The Impulse Response and Convolution / Stability / Frequency Response / Software Applications / Chapter Summary / Problems
3. The DFT and Spectral Analysis
Motivation / The Discrete-Time Fourier Transform (DTFT). The Discrete Fourier Transform (DFT). DFT Properties. The Fast Fourier Transform (FFT). White Noise. Discrete-Time Frequency Response. Zero Padding. Power Density Spectrum Estimation. The Spectrogram. Software Applications. Chapter Summary. Problems.
4. Convolution and Correlation
Motivation / Convolution / Fast Convolution / Cross-Correlation / Fast Correlation / Auto-Correlation / Extracting Periodic Signals from Noise / Software Applications / Chapter Summary / Problems
5. Filter Specifications and Structures
Motivation. Filter Design Specifications. Linear-Phase Filters. Minimum-Phase and Allpass Filters. FIR Filter Realization Structures. IIR Filter Realization Structures. FIR Finite Word Length Effects. IIR Finite Word Length Effects. Software Applications. Chapter Summary. Problems.
6. FIR Filter Design
Motivation / Windowing Method / Frequency Sampling Method / Least Squares Method / Optimal Equiripple Method / Differentiators and Hilbert Transformers / Software Applications / Chapter Summary / Problems
7. Multirate Signal Processing
Motivation / Integer Decimators and Interpolators / Rational Sampling Rate Converters / Multirate Filter Realization Structures / Subband Processing / Oversampling ADC / Oversampling DAC / Software Applications / Chapter Summary / Problems
8. IIR Filter Design
Motivation / Filter Design by Pole-Zero Placement / Filter Design Parameters / Classical Analog Filters / Bilinear Transformation Method / Frequency Transformations / Software Applications / Chapter Summary / Problems
9. Adaptive Signal Processing
Motivation / Mean Square Error / The Least Mean Square (LMS) Method / Performance Analysis of the LMS Method / Modified LMS Methods / Adaptive FIR Filter Design / The Recursive Least Squares (RLS) Method / Active Noise Control / Nonlinear System Identification / Software Applications / Chapter Summary / Problems
APPENDICES:
1. MATLAB
Workspace / Variables and Initialization / Mathematical Operators / Input and Output / Branching and Loops / Built-In Functions / User-Defined Functions / GUIs
2. FDSP Toolbox
Installation / Driver Module f_dsp / Chapter GUI Modules / FDSP Toolbox Functions
3. Transform Tables
Fourier Series / Fourier Transform / Laplace Transform / Z-Transform / Discrete-Time Fourier Transform (DTFT), Discrete Fourier Transform (DFT)
4. Mathematical Identifies
Complex Numbers / Euler''s Identity / Trigonometric Identities / Inequalities