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Stochastic computing = techniques an...

Gross, Warren J.

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Stochastic computing = techniques and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Stochastic computing/ edited by Warren J. Gross, Vincent C. Gaudet.
Reminder of title:	techniques and applications /
other author:	Gross, Warren J.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xvi, 215 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Foreword: Gulak -- 1. Introduction to Stochastic Computing (Gaudet, Gross, Smith) -- 2. Origins of Stochastic Computing (Gaines) -- 3. Tutorial on Stochastic Computing (Winstead) -- 4. Accuracy and Correlation in Stochastic Computing (Alaghi, Ting, Lee, Hayes) -- 5. Synthesis of Polynomial Functions (Riedel, Qian) -- 6. Deterministic Approaches to Bitstream Computing (Riedel) -- 7. Generating Stochastic Bitstreams (Hsiao, Anderson, Hara-Azumi) -- 8. RRAM Solutions for Stochastic Computing (Knag, Gaba, Lu, Zhang) -- 9 Spintronic Solutions for Stochastic Computing (Jia, Wang, Huang, Zhang, Yang, Qu, et al.) -- 10. Brain-inspired computing (Onizawa, Gross, Hanyu) -- 11. Stochastic Decoding of Error-Correcting Codes (Leduc-Primeau, Hemati, Gaudet, Gross)
Contained By:	Springer eBooks
Subject:	Probabilistic automata. -
Online resource:	https://doi.org/10.1007/978-3-030-03730-7
ISBN:	9783030037307

Stochastic computing = techniques and applications /
Stochastic computingtechniques and applications /[electronic resource] :edited by Warren J. Gross, Vincent C. Gaudet. - Cham :Springer International Publishing :2019. - xvi, 215 p. :ill. (some col.), digital ;24 cm.

Foreword: Gulak -- 1. Introduction to Stochastic Computing (Gaudet, Gross, Smith) -- 2. Origins of Stochastic Computing (Gaines) -- 3. Tutorial on Stochastic Computing (Winstead) -- 4. Accuracy and Correlation in Stochastic Computing (Alaghi, Ting, Lee, Hayes) -- 5. Synthesis of Polynomial Functions (Riedel, Qian) -- 6. Deterministic Approaches to Bitstream Computing (Riedel) -- 7. Generating Stochastic Bitstreams (Hsiao, Anderson, Hara-Azumi) -- 8. RRAM Solutions for Stochastic Computing (Knag, Gaba, Lu, Zhang) -- 9 Spintronic Solutions for Stochastic Computing (Jia, Wang, Huang, Zhang, Yang, Qu, et al.) -- 10. Brain-inspired computing (Onizawa, Gross, Hanyu) -- 11. Stochastic Decoding of Error-Correcting Codes (Leduc-Primeau, Hemati, Gaudet, Gross)

This book covers the history and recent developments of stochastic computing. Stochastic computing (SC) was first introduced in the 1960s for logic circuit design, but its origin can be traced back to von Neumann's work on probabilistic logic. In SC, real numbers are encoded by random binary bit streams, and information is carried on the statistics of the binary streams. SC offers advantages such as hardware simplicity and fault tolerance. Its promise in data processing has been shown in applications including neural computation, decoding of error-correcting codes, image processing, spectral transforms and reliability analysis. There are three main parts to this book. The first part, comprising Chapters 1 and 2, provides a history of the technical developments in stochastic computing and a tutorial overview of the field for both novice and seasoned stochastic computing researchers. In the second part, comprising Chapters 3 to 8, we review both well-established and emerging design approaches for stochastic computing systems, with a focus on accuracy, correlation, sequence generation, and synthesis. The last part, comprising Chapters 9 and 10, provides insights into applications in machine learning and error-control coding.

ISBN: 9783030037307

Standard No.: 10.1007/978-3-030-03730-7doiSubjects--Topical Terms:

3385456
Probabilistic automata.

LC Class. No.: QA267.5.P7 / S763 2019

Dewey Class. No.: 003.76

Stochastic computing = techniques and applications /
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245 0 0 $a Stochastic computing $h [electronic resource] : $b techniques and applications / $c edited by Warren J. Gross, Vincent C. Gaudet.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xvi, 215 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Foreword: Gulak -- 1. Introduction to Stochastic Computing (Gaudet, Gross, Smith) -- 2. Origins of Stochastic Computing (Gaines) -- 3. Tutorial on Stochastic Computing (Winstead) -- 4. Accuracy and Correlation in Stochastic Computing (Alaghi, Ting, Lee, Hayes) -- 5. Synthesis of Polynomial Functions (Riedel, Qian) -- 6. Deterministic Approaches to Bitstream Computing (Riedel) -- 7. Generating Stochastic Bitstreams (Hsiao, Anderson, Hara-Azumi) -- 8. RRAM Solutions for Stochastic Computing (Knag, Gaba, Lu, Zhang) -- 9 Spintronic Solutions for Stochastic Computing (Jia, Wang, Huang, Zhang, Yang, Qu, et al.) -- 10. Brain-inspired computing (Onizawa, Gross, Hanyu) -- 11. Stochastic Decoding of Error-Correcting Codes (Leduc-Primeau, Hemati, Gaudet, Gross)
520 $a This book covers the history and recent developments of stochastic computing. Stochastic computing (SC) was first introduced in the 1960s for logic circuit design, but its origin can be traced back to von Neumann's work on probabilistic logic. In SC, real numbers are encoded by random binary bit streams, and information is carried on the statistics of the binary streams. SC offers advantages such as hardware simplicity and fault tolerance. Its promise in data processing has been shown in applications including neural computation, decoding of error-correcting codes, image processing, spectral transforms and reliability analysis. There are three main parts to this book. The first part, comprising Chapters 1 and 2, provides a history of the technical developments in stochastic computing and a tutorial overview of the field for both novice and seasoned stochastic computing researchers. In the second part, comprising Chapters 3 to 8, we review both well-established and emerging design approaches for stochastic computing systems, with a focus on accuracy, correlation, sequence generation, and synthesis. The last part, comprising Chapters 9 and 10, provides insights into applications in machine learning and error-control coding.
650 0 $a Probabilistic automata. $3 3385456
650 0 $a Stochastic programming. $3 647620
650 1 4 $a Circuits and Systems. $3 896527
650 2 4 $a Logic Design. $3 892735
650 2 4 $a Probability Theory and Stochastic Processes. $3 891080
700 1 $a Gross, Warren J. $3 3251588
700 1 $a Gaudet, Vincent C. $3 3385455
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-3-030-03730-7
950 $a Engineering (Springer-11647)