LEADER 04077nam 22005775 450 001 9910337627603321 005 20200706050847.0 010 $a3-030-03730-4 024 7 $a10.1007/978-3-030-03730-7 035 $a(CKB)4100000007656764 035 $a(DE-He213)978-3-030-03730-7 035 $a(MiAaPQ)EBC5926196 035 $a(PPN)235006769 035 $a(EXLCZ)994100000007656764 100 $a20190218d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStochastic Computing: Techniques and Applications /$fedited by Warren J. Gross, Vincent C. Gaudet 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XVI, 215 p. 133 illus., 34 illus. in color.) 311 $a3-030-03729-0 320 $aIncludes bibliographical references. 327 $aForeword: 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). 330 $aThis 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. 606 $aElectronic circuits 606 $aLogic design 606 $aProbabilities 606 $aCircuits and Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/T24068 606 $aLogic Design$3https://scigraph.springernature.com/ontologies/product-market-codes/I12050 606 $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004 615 0$aElectronic circuits. 615 0$aLogic design. 615 0$aProbabilities. 615 14$aCircuits and Systems. 615 24$aLogic Design. 615 24$aProbability Theory and Stochastic Processes. 676 $a620.001171 676 $a003.76 702 $aGross$b Warren J$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGaudet$b Vincent C$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910337627603321 996 $aStochastic Computing: Techniques and Applications$91935509 997 $aUNINA