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710	2		_aSpringerLink (Online service) _9106996
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008			190218s2019 gw a o |||| 0|eng d
020			_a9783030037307
024	7		_a10.1007/978-3-030-03730-7 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aT57.79 _b2019 EB
245	0	0	_aStochastic Computing : _bTechniques and Applications _cedited by Warren J. Gross, Vincent C. Gaudet
264		1	_aCham _bSpringer _c2019
300			_a1 recurso en línea (XVI, 215 páginas) _b133 ilustraciones, 34 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aEngineering (Springer-11647)
505	0		_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).
520	3		_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.
988			_aPrimersemestre_2019_Engineering
650		7	_2embne _9670357 _aProgramación estocástica
700	1		_aGaudet, Vincent C. _eeditor literario _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aGross, Warren J. _eeditor literario _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030037291
776	0	8	_iPrinted edition: _z9783030037314
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-03730-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aSI _cm _dz _feng _ggw _h0 _b08/2019 _eu _zSI