Digital Signal Processing 101

Michael Parker

ISBN 10: 0128114533 / ISBN 13: 9780128114537

Published by Elsevier Science Jun 2017, 2017

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -Digital Signal Processing 101: Everything You Need to Know to Get Started provides a basic tutorial on digital signal processing (DSP). Beginning with discussions of numerical representation and complex numbers and exponentials, it goes on to explain difficult concepts such as sampling, aliasing, imaginary numbers, and frequency response. It does so using easy-to-understand examples with minimum mathematics. In addition, there is an overview of the DSP functions and implementation used in several DSP-intensive fields or applications, from error correction to CDMA mobile communication to airborne radar systems. This book has been updated to include the latest developments in Digital Signal Processing, and has eight new chapters on: Automotive Radar Signal Processing Space-Time Adaptive Processing Radar Field Orientated Motor Control Matrix Inversion algorithms GPUs for computing Machine Learning Entropy and Predictive Coding Video compression Features eight new chapters on Automotive Radar Signal Processing, Space-Time Adaptive Processing Radar, Field Orientated Motor Control, Matrix Inversion algorithms, GPUs for computing, Machine Learning, Entropy and Predictive Coding, and Video compression Provides clear examples and a non-mathematical approach to get you up to speed quickly Includes an overview of the DSP functions and implementation used in typical DSP-intensive applications, including error correction, CDMA mobile communication, and radar systems 432 pp. Englisch.

Seller Inventory # 9780128114537

Bibliographic Details

• Title: Digital Signal Processing 101
• Publisher: Elsevier Science Jun 2017
• Publication Date: 2017
• Language: English
• ISBN 10: 0128114533
• ISBN 13: 9780128114537
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 233W x 189H x 25D millimeters 233 millimeters width by 189 millimeters height by 25 millimeters depth
• Weight: 906 grams

About this title

Synopsis

Digital Signal Processing 101: Everything You Need to Know to Get Started provides a basic tutorial on digital signal processing (DSP). Beginning with discussions of numerical representation and complex numbers and exponentials, it goes on to explain difficult concepts such as sampling, aliasing, imaginary numbers, and frequency response. It does so using easy-to-understand examples with minimum mathematics. In addition, there is an overview of the DSP functions and implementation used in several DSP-intensive fields or applications, from error correction to CDMA mobile communication to airborne radar systems.

This book has been updated to include the latest developments in Digital Signal Processing, and has eight new chapters on:

• Automotive Radar Signal Processing
• Space-Time Adaptive Processing Radar
• Field Orientated Motor Control
• Matrix Inversion algorithms
• GPUs for computing
• Machine Learning
• Entropy and Predictive Coding
• Video compression

• Features eight new chapters on Automotive Radar Signal Processing, Space-Time Adaptive Processing Radar, Field Orientated Motor Control, Matrix Inversion algorithms, GPUs for computing, Machine Learning, Entropy and Predictive Coding, and Video compression
• Provides clear examples and a non-mathematical approach to get you up to speed quickly
• Includes an overview of the DSP functions and implementation used in typical DSP-intensive applications, including error correction, CDMA mobile communication, and radar systems

About the Author

Michael Parker is responsible for Intel’s FPGA division digital signal processing (DSP) product planning. This includes Variable Precision FPGA silicon architecture for DSP applications, DSP tool development, floating point tools, IP and video IP. He joined Altera (now Intel) in January 2007, and has over 20 years of previous DSP engineering design experience with companies such as Alvarion, Soma Networks, Avalcom, TCSI, Stanford Telecom and several startup companies. He holds an MSEE from Santa Clara University, and BSEE from Rensselaer Polytechnic Institute.