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MATLAB® Software for the Code Excited Linear Prediction Algorithm: The Federal Standard-1016 de Karthikeyan Ramamurthy

MATLAB® Software for the Code Excited Linear Prediction Algorithm: The Federal Standard-1016: Synthesis Lectures on Algorithms and Software in Engineering

Autor Karthikeyan Ramamurthy, Andreas Spanias
en Limba Engleză Paperback – 4 mar 2010
This book describes several modules of the Code Excited Linear Prediction (CELP) algorithm. The authors use the Federal Standard-1016 CELP MATLAB® software to describe in detail several functions and parameter computations associated with analysis-by-synthesis linear prediction. The book begins with a description of the basics of linear prediction followed by an overview of the FS-1016 CELP algorithm. Subsequent chapters describe the various modules of the CELP algorithm in detail. In each chapter, an overall functional description of CELP modules is provided along with detailed illustrations of their MATLAB® implementation. Several code examples and plots are provided to highlight some of the key CELP concepts. Link to MATLAB® code found within the book Table of Contents: Introduction to Linear Predictive Coding / Autocorrelation Analysis and Linear Prediction / Line Spectral Frequency Computation / Spectral Distortion / The Codebook Search / The FS-1016 Decoder
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Specificații

ISBN-13: 9783031003868
ISBN-10: 3031003861
Ilustrații: IX, 99 p.
Dimensiuni: 191 x 235 mm
Greutate: 0.2 kg
Editura: Springer International Publishing
Colecția Springer
Seria Synthesis Lectures on Algorithms and Software in Engineering

Locul publicării:Cham, Switzerland

Cuprins

Introduction to Linear Predictive Coding.- Autocorrelation Analysis and Linear Prediction.- Line Spectral Frequency Computation.- Spectral Distortion.- The Codebook Search.- The FS-1016 Decoder.

Notă biografică

Karthikeyan Natesan Ramamurthy is a research staff member in the Business Solutions and Mathematical Sciences department at the IBM Thomas J. Watson Research Center in Yorktown Heights, NY. He received his M.S. and Ph.D. degrees in Electrical Engineering from Arizona State University. His research interests are in the areas of low-dimensional signal models, machine learning, data analytics, and computer vision. He has been a reviewer for a number of IEEE and Elsevier journals and conferences. Andreas Spanias is a professor in the Department of Electrical Engineering, Fulton School of Engineering at Arizona State University. He is also the director of the SenSIP consortium. His research interests are in the areas of adaptive signal processing, speech processing, and audio sensing. Prof. Spanias has collaborated with Intel Corporation, Sandia National Labs, Motorola, Texas Instruments, DTC, Freescale, Microchip, and Active Noise and Vibration Technologies. He and his student team developed the computer simulation software Java-DSP ( J-DSP; ISBN 0-9724984-0-0). He is author of two textbooks, Audio Processing and Coding by Wiley and DSP: An Interactive Approach. He received the 2003 Teaching Award from the IEEE Phoenix section for the development of J-DSP. He has served as associate editor of the IEEE Transactions on Signal Processing and as General Cochair of the 1999 International Conference on Acoustics Speech and Signal Processing (ICASSP-99) in Phoenix. He also served as the IEEE Signal Processing Vice President for Conferences and is currently member-at-large of the IEEE SPS Conference Board. Prof. Spanias is corecipient of the 2002 IEEE Donald G. Fink paper prize award and was elected fellow of the IEEE in 2003. He served as distinguished lecturer for the IEEE Signal Processing Society. He is currently the editor for the Morgan & Claypool Publishers series on DSP algorithms and software.