Signal Processing and Linear Systems

Book Description
This text presents a comprehensive treatment of signal processing and linear systems suitable for juniors and seniors in electrical engineering. Based on B. P. Lathi's widely used book, Linear Systems and Signals, it features additional applications to communications, controls, and filtering as well as new chapters on analog and digital filters and digital signal processing. Lathi emphasizes the physical appreciation of concepts rather than the mere mathematical manipulation of symbols. Avoiding the tendency to treat engineering as a branch of applied mathematics, he uses mathematics to enhance physical and intuitive understanding of concepts, instead of employing it only to prove axiomatic theory. Theoretical results are supported by carefully chosen examples and analogies, allowing students to intuitively discover meaning for themselves.

Table of Contents
Chapter 1. Introduction to Signals and Systems
Chapter 2. Time-Domain Analysis of Continuous-Time Systems
Chapter 3. Signal Representation by Fourier Series
Chapter 4. Continuous-Time Signal Analysis: The Fourier Transform
Chapter 5. Sampling
Chapter 6. Continuous-Time System Analysis Using the Laplace Transform
Chapter 7. Frequency Response and Analog Filters
Chapter 8. Discrete-Time Signals and Systems
Chapter 9. Time-Domain Analysis of Discrete-Time Systems
Chapter 10. Fourier Analysis of Discrete-Time Signals
Chapter 11. Discrete-Time System Analysis Using the Z-Transform
Chapter 12. Frequency Response and Digital Filters
Chapter 13. State-Space Analysis

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Discrete-Time Signal Processing

Book Description
THE definitive, authoritative book on DSP -- ideal for those with an introductory-level knowledge of signals and systems. Written by prominent, DSP pioneers, it provides thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete-time Fourier Analysis. By focusing on the general and universal concepts in discrete-time signal processing, it remains vital and relevant to the new challenges arising in the field -- "without" limiting itself to specific technologies with relatively short life spans.

Table of Contents
1. Introduction
2. Discrete Time-Signals and Systems
3. The z-Transform
4. Sampling of Continuous-Time Signals
5. Transform Analysis of Linear Time-Invariant Systems
6. Structures for Discrete-Time Systems
7. Filter Design Techniques
8. The Discrete Fourier Transform
9. Computation of the Discrete Fourier Transform
10. Fourier Analysis of Signals Using the Discrete Fourier Transform
11. Discrete Hilbert Transforms

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Digital Filter Design (Online E-book)

Book Description
The purpose of this book is to provide you with different theorethical and practical approaches to digital filter design. The book covers design of both finite and infinite impulse response filters. In addition, it applies the most popular and most commonly used design methodes giving the best solutions. Intuitive explanations and numerous examples contained herein will help you to devolope your understanding of these methods and test your knowledge on concrete issues.

Table of Contents
Chapter 1: Basic concepts of digital filtering and types of digital filters
Chapter 2: FIR filters
Chapter 3: IIR filters

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Signal Processing First

Book Description
Designed and written by experienced and well-respected authors, this hands on, multi-media package provides a motivating introduction to fundamental concepts, specifically discrete-time systems. Unique features such as visual learning demonstrations, MATLAB laboratories and a bank of solved problems are just a few things that make this an essential learning tool for mastering fundamental concepts in today's electrical and computer engineering forum. Covers basic DSP concepts, integrated laboratory projects—related to music, sound and image processing. Other topics include new MATLAB functions for basic DSP operations, Sinusoids, Spectrum Representation, Sampling and Aliasing, FIR Filters, Frequency Response of FIR Filters, z-Transforms, IIR Filters, and Spectrum Analysis. Useful as a self-teaching tool for anyone eager to discover more about DSP applications, multi-media signals, and MATLAB.

Table of Contents
1. Introduction.
2. Sinusoids.
3. Spectrum Representation.
4. Sampling and Aliasing.
5. FIR Filters.
6. Frequency Response of FIR Filters.
7. z-Transforms.
8. IIR Filters.
9. Continuous-Time Signals and LTI Systems.
10. The Frequency Response.
11. Continuous-Time Fourier Transform.
12. Filtering, Modulation, and Sampling.
13. Computing the Spectrum.

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Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
OTHER RESOURCES

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EEG Signal Processing

Book Description
Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormalities. With appropriate interpretation methods they are emerging as a key methodology to satisfy the increasing global demand for more affordable and effective clinical and healthcare services.
Developing and understanding advanced signal processing techniques for the analysis of EEG signals is crucial in the area of biomedical research. This book focuses on these techniques, providing expansive coverage of algorithms and tools from the field of digital signal processing. It discusses their applications to medical data, using graphs and topographic images to show simulation results that assess the efficacy of the methods.

Additionally, expect to find:
- explanations of the significance of EEG signal analysis and processing (with examples) and a useful theoretical and mathematical background for the analysis and processing of EEG signals;
- an exploration of normal and abnormal EEGs, neurological symptoms and diagnostic information, and representations of the EEGs;
- reviews of theoretical approaches in EEG modelling, such as restoration, enhancement, segmentation, and the removal of different internal and external artefacts from the EEG and ERP (event-related potential) signals;
- coverage of major abnormalities such as seizure, and mental illnesses such as dementia, schizophrenia, and Alzheimer’s disease, together with their mathematical interpretations from the EEG and ERP signals and sleep phenomenon;
- descriptions of nonlinear and adaptive digital signal processing techniques for abnormality detection, source localization and brain-computer interfacing using multi-channel EEG data with emphasis on non-invasive techniques, together with future topics for research in the area of EEG signal processing.

The information within EEG Signal Processing has the potential to enhance the clinically-related information within EEG signals, thereby aiding physicians and ultimately providing more cost effective, efficient diagnostic tools. It will be beneficial to psychiatrists, neurophysiologists, engineers, and students or researchers in neurosciences. Undergraduate and postgraduate biomedical engineering students and postgraduate epileptology students will also find it a helpful reference.

Table of Contents
1 Introduction to EEG
2 Fundamentals of EEG Signal Processing
3 Event-Related Potentials
4 Seizure Signal Analysis
5 EEG Source Localization
6 Sleep EEG
7 Brain Computer Interfacing

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Programming dsPIC MCU in C (Online E-Book)

Book Overview
Learn how to write a program on your own, how to debug it, and how to use it to start up a microcontroller. The book provides numerous practical examples with necessary connection schematics explaining the operation of temperature sensors, A/D and D/A converters, LCD and LED displays, relays, communication modules etc. It is constantly updated with fresh examples. All program codes are commented in details to make it easier for beginners to start programming. Instruction set, operators, control structures, and other elements of the C programming language are thoroughly explained as well. And that's not all, the book also includes a useful appendix on the mikroC for dsPIC development environment, instructions on how to install it and how to use it to its full potential.

Contents
    Chapter 1: Introduction
    Chapter 2: Configuration Bits
    Chapter 3: Interrupts and Traps
    Chapter 4: Timers
    Chapter 5: Input Capture
    Chapter 6: Output Compare Module
    Chapter 7: A/D Converter
    Chapter 8: Memory Model
    Chapter 9: SPI Module
    Chapter 10: UART Module
    Chapter 11: DSP Engine
    Chapter 12: I2C (Inter Integrated Circuit) module
    Chapter 13: Examples
    Chapter 14: DSP Examples
    Chapter 15: Digital filter design

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A Wavelet Tour Of Signal Processing by Mallat, 2nd Edition

Contents:
Chapter - 1: INTRODUCTION  TO  A  TRANSIENT  WORLD
Chapter - 2: FOURIER  KINGDOM
Chapter - 3: DISCRETE  REVOLUTION
Chapter - 4: TIME  MEETS  FREQUENCY
Chapter - 5: FRAMES
Chapter - 6: WAVELET  ZOOM
Chapter - 7: WAVELET  BASES
Chapter - 8: WAVELET  PACKET AND  LOCAL  COSINE  BASES
Chapter - 9: AN  APPROXIMATION  TOUR
Chapter - 10: ESTIMATIONS  ARE  APPROXIMATIONS
Chapter - 11: TRANSFORM  CODING
Appendix A : MATHEMATICAL  COMPLEMENTS
Appendix B : SOFTWARE  TOOLBOXES

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Adaptive Filter Theory by Simon Haykin

Introduction:
Adaptive Filter Theory looks at both the mathematical theory behind various linear adaptive filters with finite-duration impulse response (FIR) and the elements of supervised neural networks. Up-to-date and in-depth treatment of adaptive filters develops concepts in a unified and accessible manner. This highly successful book provides comprehensive coverage of adaptive filters in a highly readable and understandable fashion. Includes an extensive use of illustrative examples; and MATLAB experiments, which illustrate the practical realities and intricacies of adaptive filters, the codes for which can be downloaded from the Web. Covers a wide range of topics including Stochastic Processes, Wiener Filters, and Kalman Filters. For those interested in learning about adaptive filters and the theories behind them.

Contents:
1. Stochastic Processes and Models.
 2. Wiener Filters.
 3. Linear Prediction.
 4. Method of Steepest Descent.
 5. Least-Mean-Square Adaptive Filters.
 6. Normalized Least-Mean-Square Adaptive Filters.
 7. Transform-Domain and Sub-Band Adaptive Filters.
 8. Method of Least Squares.
 9. Recursive Least-Square Adaptive Filters.
10. Kalman Filters as the Unifying Bases for RLS Filters.
11. Square-Root Adaptive Filters.
12. Order-Recursive Adaptive Filters.
13. Finite-Precision Effects.
14. Tracking of Time-Varying Systems.
15. Adaptive Filters Using Infinite-Duration Impulse Response Structures.
16. Blind Deconvolution.
17. Back-Propagation Learning.

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