Digital Signal Processing, Second Edition enables electrical engineers and technicians in the fields of biomedical, computer, and electronics engineering to master the essential fundamentals of DSP principles and practice. Many instructive worked examples are used to illustrate the material, and the use of mathematics is minimized for easier grasp of concepts. As such, this title is also useful to undergraduates in electrical engineering, and as a reference for science students and practicing engineers. The book goes beyond DSP theory, to show implementation of algorithms in hardware and software. Additional topics covered include adaptive filtering with noise reduction and echo cancellations, speech compression, signal sampling, digital filter realizations, filter design, multimedia applications, over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as PCM, u-law, ADPCM, and multi-rate DSP and over-sampling ADC. New to this edition: - MATLAB projects dealing with practical applications added throughout the book - New chapter (chapter 13) covering sub-band coding and wavelet transforms, methods that have become popular in the DSP field - New applications included in many chapters, including applications of DFT to seismic signals, electrocardiography data, and vibration signals - All real-time C programs revised for the TMS320C6713 DSK - Covers DSP principles with emphasis on communications and control applications - Chapter objectives, worked examples, and end-of-chapter exercises aid the reader in grasping key concepts and solving related problems - Website with MATLAB programs for simulation and C programs for real-time DSP

Real-time Digital Signal Processing: Implementations and Applications has been completely updated and revised for the 2nd edition and remains the only book on DSP to provide an overview of DSP theory and programming with hands-on experiments using MATLAB, C and the newest fixed-point processors from Texas Instruments (TI).

About the Book : - Digital Signal Processing Fundamentals Digital Signal Processing (DSP), as the term suggests, is the processing of signals using digital computers. These signals might be anything transferred from an analog domain to a digital form (e.g., temperature and pressure sensors, voices over a telephone, images from a camera, or data transmittal though computes). As a result, understanding the whole spectrum of DSP technology can be a daunting task for electrical engineering professionals and students alike. Digital Signal Processing Fundamentals provides a comprehensive look at DSP by introducing the important mathematical processes and then providing several application-specific tutorials for practicing the techniques learned. Beginning with general theory, including Fourier Analysis, the mathematics of complex numbers, Fourier transforms, differential equations, analog and digital filters, and much more; the book then delves into Matlab and Scilab tutorials with examples on solving practical engineering problems, followed by software applications on image processing and audio processing - complete with all the algorithms and source code. This is an invaluable resource for anyone seeking to understand how DSP works. Features: Provides a comprehensive overview and introduction of digital signal processing technology. Provides application with software algorithms Explains the concept of Nyquist frequency, orthogonal functions and method of finding Fourier coefficients Includes a CD-ROM with the source code for the projects plus Matlab and Scilab that generate graphs, figures in the book, and third party application software Discusses the techniques of digital filtering and windowing of input data, including: Butterwoth, Chebyshev, and elliptic filter formulation. Table Of Contents : Fourier Analysis Complex Number Arithmetic The Fourier Transform Solutions of Differential Equations Laplace Transforms and z-Tranforms Filter Design Digital Filters The FIR Filters Appendix A : Matlab Tutorial Appendix B : Scilab Tutorial Appendix C : Digital Filter Applications Appendix D : About the CD-ROM Appendix E : Software Licenses Appendix F : Bibliography Index About Author :- Ashfaq A. Khan (Baton Rouge, LA) is a senior software engineer for LIGO Livingston Observatory, with over 20 years of experience in system design. He has conducted several workshop and is the author of Practical Linux Programming: Device Drivers, Embedded Systems, and the Internet.

This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localization, the limitations of uncertainty, and computational costs. It includes over 160 homework problems and over 220 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, including Mathematica® resources and interactive demonstrations.

Using everyday examples and simple diagrams, two leading DSP consultants and instructors completely demystify signal processing with this text. Students will discover what digital signals are, how they're generated, and how they're changing life. Students will learn all they need to know about digital signal collection, filtering, analysis, and more, and how DSP works in today's most exciting devices and applications.

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material. You’ll explore: Periodic signals and their spectrums Harmonic structure of simple waveforms Chirps and other sounds whose spectrum changes over time Noise signals and natural sources of noise The autocorrelation function for estimating pitch The discrete cosine transform (DCT) for compression The Fast Fourier Transform for spectral analysis Relating operations in time to filters in the frequency domain Linear time-invariant (LTI) system theory Amplitude modulation (AM) used in radio Other books in this series include Think Stats and Think Bayes, also by Allen Downey.

In addition to its thorough coverage of DSP design and programming techniques, Smith also covers the operation and usage of DSP chips. He uses Analog Devices' popular DSP chip family as design examples. - Covers all major DSP topics - Full of insider information and shortcuts - Basic techniques and algorithms explained without complex numbers