Signal Processing/Introduction

What is Signal Processing?
The field of signal processing is a very important field of study and one that makes possible various other fields such as communications. MP3 music files contain processed, transformed, and compressed music signal data. Speech recognition systems such as dictation software need to analyze and process signal data to identify individual words in a spoken sentence. Neural interface devices, such as various medical prostheses must read the complicated signals of neurons, process those signals to determine the important features, and then convert those features to digital data. Signal processing enables high-speed data communication, even in the presence of interference or noise.

Who is This Book For?
This book is intended for readers at the undergraduate and graduate college levels, specifically those studying electrical engineering or a related field. This book can be used to accompany several semesters of study, depending on how the material is divided and presented.

What are the Prerequisites?
All readers should have significant prior knowledge of Signals and Systems, probability, Linear Algebra, and Calculus. Knowledge of linear algebra topics covered in Engineering Analysis, especially the sections about probability are required. Readers who do not have the necessary mathematics background will be at a severe disadvantage.

What Will This Book Cover?
This book will take a look at the traditional problems and methods of signal processing. We will attempt to cover many analog processing techniques, but we also must cover many advanced digital techniques as well. The Digital Signal Processing book will lay many foundations about digital systems that will be used in this book. The reader is strongly encouraged to either read both these books simultaneously, or to read the beginning sections of Digital Signal Processing first before reading this book. That book will cover many topics that are specific to digital systems, while this book will attempt to cover techniques that are useful for either analog or digital, are hybrid in nature (that they have analog and digital components) or that are traditionally analog but that can be modified for fast digital computation.

This book will attempt to cover the concept of filtering specifically, including adaptive Weiner and Kalman filters. This book will also look at some offshoots of adaptive filter theory, including beamforming. The more advanced sections of this book will look at additional subject, such as nonlinear systems and wavelet analysis.

This book will not cover, and will not attempt to cover, prerequisite information that is already covered in the Signals and Systems book or any of the other prerequisites. This includes, but is not limited to:
 * Integral or differential calculus
 * Differential equations
 * Digital systems and difference equations
 * LTI systems theory
 * Stochastic signals or processes
 * Fourier transform and fourier series