Digital Signal Processing Algorithms: Number Theory, Convolution, Fast Fourier Transforms, and Applications

Digital Signal Processing Algorithms describes computational number theory and its applications to deriving fast algorithms for digital signal processing. It demonstrates the importance of computational number theory in the design of digital signal processing algorithms and clearly describes the nature and structure of the algorithms themselves. The book has two primary focuses: first, it establishes the properties of discrete-time sequence indices and their corresponding fast algorithms; and second, it investigates the properties of the discrete-time sequences and the corresponding fast algorithms for processing these sequences.
Digital Signal Processing Algorithms examines three of the most common computational tasks that occur in digital signal processing; namely, cyclic convolution, acyclic convolution, and discrete Fourier transformation. The application of number theory to deriving fast and efficient algorithms for these three and related computationally intensive tasks is clearly discussed and illustrated with examples.
Its comprehensive coverage of digital signal processing, computer arithmetic, and coding theory makes Digital Signal Processing Algorithms an excellent reference for practicing engineers. The authors' intent to demystify the abstract nature of number theory and the related algebra is evident throughout the text, providing clear and precise coverage of the quickly evolving field of digital signal processing.

"1113112189"
Digital Signal Processing Algorithms: Number Theory, Convolution, Fast Fourier Transforms, and Applications

Digital Signal Processing Algorithms describes computational number theory and its applications to deriving fast algorithms for digital signal processing. It demonstrates the importance of computational number theory in the design of digital signal processing algorithms and clearly describes the nature and structure of the algorithms themselves. The book has two primary focuses: first, it establishes the properties of discrete-time sequence indices and their corresponding fast algorithms; and second, it investigates the properties of the discrete-time sequences and the corresponding fast algorithms for processing these sequences.
Digital Signal Processing Algorithms examines three of the most common computational tasks that occur in digital signal processing; namely, cyclic convolution, acyclic convolution, and discrete Fourier transformation. The application of number theory to deriving fast and efficient algorithms for these three and related computationally intensive tasks is clearly discussed and illustrated with examples.
Its comprehensive coverage of digital signal processing, computer arithmetic, and coding theory makes Digital Signal Processing Algorithms an excellent reference for practicing engineers. The authors' intent to demystify the abstract nature of number theory and the related algebra is evident throughout the text, providing clear and precise coverage of the quickly evolving field of digital signal processing.

225.49 In Stock
Digital Signal Processing Algorithms: Number Theory, Convolution, Fast Fourier Transforms, and Applications

Digital Signal Processing Algorithms: Number Theory, Convolution, Fast Fourier Transforms, and Applications

by Hari Krishna
Digital Signal Processing Algorithms: Number Theory, Convolution, Fast Fourier Transforms, and Applications

Digital Signal Processing Algorithms: Number Theory, Convolution, Fast Fourier Transforms, and Applications

by Hari Krishna

eBook

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Overview

Digital Signal Processing Algorithms describes computational number theory and its applications to deriving fast algorithms for digital signal processing. It demonstrates the importance of computational number theory in the design of digital signal processing algorithms and clearly describes the nature and structure of the algorithms themselves. The book has two primary focuses: first, it establishes the properties of discrete-time sequence indices and their corresponding fast algorithms; and second, it investigates the properties of the discrete-time sequences and the corresponding fast algorithms for processing these sequences.
Digital Signal Processing Algorithms examines three of the most common computational tasks that occur in digital signal processing; namely, cyclic convolution, acyclic convolution, and discrete Fourier transformation. The application of number theory to deriving fast and efficient algorithms for these three and related computationally intensive tasks is clearly discussed and illustrated with examples.
Its comprehensive coverage of digital signal processing, computer arithmetic, and coding theory makes Digital Signal Processing Algorithms an excellent reference for practicing engineers. The authors' intent to demystify the abstract nature of number theory and the related algebra is evident throughout the text, providing clear and precise coverage of the quickly evolving field of digital signal processing.


Product Details

ISBN-13: 9781351454964
Publisher: CRC Press
Publication date: 11/22/2017
Series: Computer Science & Engineering
Sold by: Barnes & Noble
Format: eBook
Pages: 672
File size: 49 MB
Note: This product may take a few minutes to download.

About the Author

Hari Krishna

Table of Contents

Introduction. Computational Number Theory. Polynomial Algebra. Theoretical Aspects of Discrete Fourier Transform and Convolution. Cyclotomic Polynomial Factorization and Associated Fields. Cyclotomic Polynomial Factorization Over Finite Fields. Finite Integer Rings: Polynomial Algebra and Cyclotomic Factorization. Fast Algorithms For Acyclic Convolution of Discrete Sequences. Fast Algorithms for Cyclic Convolution. Discrete Fourier Transforms. A Coding Theory Framework for Error Control and Fault Tolerant Computing. Index. NTI/Sales Copy (NTI already done and approved)
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