Digital Signal Processing: A Practical Approach - Tapa dura

Acerca del autor

Emmanuel Ifeachor is Professor of Intelligent Electronic Systems and Director of the Centre for Communications, Networks and Information Systems at the University of Plymouth, UK.

Barrie Jervis is Professor of Electronic Engineering at Sheffield Hallam University, UK.

This book evolved from the authors' extensive experience in teaching practically oriented courses in DSP to both undergraduates and engineers in industry. Their own research in applied DSP has influenced the contents of the book and provided many of the examples and case studies.

De la contraportada

The second edition of this popular text continues to provide practical coverage of the fundamentals of digital signal processing (DSP) using real-world applications and practical examples to illustrate key topics. Bridging the gap between theory and practice, the text also provides insight and guidance on how to use DSP techniques in order to design real engineering systems. This edition has been updated to include new topics of increasing importance to industry, as well as revising existing material to ensure currency and maximise clarity. MATLAB-based examples and exercises are now provided with the text and further problems have been added. This practical, introductory text covers most aspects of DSP found in undergraduate electrical, electronic or communications engineering courses. It additionally covers a number of DSP techniques, such as adaptive filtering and multirate processing, which are of particular relevance to those in industry or undertaking advanced studies. Key features

• Practical examples and real-world applications illustrate DSP techniques
• Mathematical content reduced to that necessary for comprehension
• C language implementation of many DSP algorithms and functions

• MATLAB-based examples and exercises included throughout
• Coverage of analogue I/O interface techniques for real-time DSP systems
• Increased coverage of new DSP processor architectures and hardware
• New topics on system identification, deconvolution, wavelet transform and parametric spectrum analysis
• Provides practical guidance and examples for DSP systems design
• Includes current applications in audio, medical and telecommunications engineering