Introduction to Signal Processing, 2/e (2023)

Sophocles J. Orfanidis
ECE Department, Rutgers University
orfanidi@rutgers.edu

The new edition is freely available in the following PDF formats:

A printed size-6x9 paperback version is also available, but divided into two volumes due to printing limitations:

The list of references, appendices, and index are included only in volume two.

Description

The contents of the first edition have been left essentially unchanged with some minor changes. Several new topics have been added covering additional theory as well as a range of signal processing applications. Some of the new material is adapted from the author's EWA and AOSP books. New topics include:

Lattice filters
Elliptic filter design
High-order digital parametric audio equalizers
Short-time Fourier transform (STFT) and applications
Phase vocoder, time-scale and pitch-scale modification
DCT, MDCT, Princen-Bradley windows, data compression
Discrete wavelet transforms, wavelet denoising
Discretization methods for continuous-time systems
Brief introduction to analog and digital PID control systems
Local polynomial filters
Minimum-roughness Henderson filters
Weighted local polynomial modeling and LOESS
Local polynomial interpolation
Exponential moving average filters
Local-level, local-slope, local-acceleration filters
Zero-lag filters
Filtering methods in financial markets
Moving Average Filters - SMA, WMA, TMA, EMA
Predictive moving average filters
Single, double, triple EMA indicators
Linear regression and R-square indicators
Moving average filters with reduced lag
Zig-zag indicators
Envelopes, bands, channels, parabolic SAR
Momentum, oscillators, and other market indicators
Markowitz mean-variance portfolio theory, efficient frontier
Whittaker-Henderson smoothing including sparse versions
Hodrick-Prescott filters
Sparse modeling - LASSO and BPDN
Periodic signal extraction
Fractional delay filters
Signal averaging
Ideal and classical seasonal decomposition
Census X-11 decomposition filters
Seasonal Whittaker-Henderson decomposition including sparse versions
Brief introduction to neural networks
Prolate spheroidal wave functions and applications

Supplementary Materials

Materials from the Spring-2021 graduate course 332:521 Digital Signal Analytics (formerly, Digital Signals & Filters) provide supplementary materials for the new edition:

syllabus and class notes
computer projects

MATLAB Toolbox

The zipped file ISP2e-toolbox.zip (May 2023) contains MATLAB functions, examples, and data files, and combines functions from the author's I2SP, AOSP, and EWA toolboxes.

Copyright Notices

Links to the book's web page, http://www.ece. rutgers.edu/~orfanidi/intro2sp/2e , may be placed on any web site. Any part of this book (including the supplementary class notes and computer projects) may be downloaded and printed for personal or educational use only, as long as the printed or photocopied pages are not altered in any way from the original PDF filse posted on the book's web page.

No part of this book may be reproduced, altered in any way, or transmitted in any form for commercial, profit, sale, or marketing purposes.

MATLAB^® is a registered trademark of The MathWorks, Inc.

CVX software by Michael Grant and Stephen Boyd, CVX: Matlab software for disciplined convex programming, version 2.0 beta, Sept. 2013.

Some example audio files were used from the following resources:
Udo Zölzer (ed.), DAFX - Digital Audio Effects, Wiley, 2002, MATLAB files.
Robin N. Strickland, ECE 429/529, Digital Signal Processing course, Spring 2009, audio files.

September 2023 - direct links to my online books and some past courses may be found here.