000 | 04134nam a22005775i 4500 | ||
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001 | 978-981-99-5072-0 | ||
003 | DE-He213 | ||
005 | 20240423130148.0 | ||
007 | cr nn 008mamaa | ||
008 | 231016s2024 si | s |||| 0|eng d | ||
020 |
_a9789819950720 _9978-981-99-5072-0 |
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024 | 7 |
_a10.1007/978-981-99-5072-0 _2doi |
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050 | 4 | _aQ334-342 | |
050 | 4 | _aTA347.A78 | |
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_aUYQ _2bicssc |
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_aPhotonic Neural Networks with Spatiotemporal Dynamics _h[electronic resource] : _bParadigms of Computing and Implementation / _cedited by Hideyuki Suzuki, Jun Tanida, Masanori Hashimoto. |
250 | _a1st ed. 2024. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2024. |
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300 |
_aVIII, 278 p. 128 illus., 108 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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505 | 0 | _aRevival of Optical Computing -- Nonlinear Dynamics of Recurrent Neural Networks for Computing -- Fluorescence Energy Transfer Computing -- Quantum-Dot Based Photonic Reservoir Computing -- Exploring Integrated Device Implementation for FRET-based Optical Reservoir Computing -- FRET Networks -- Quantum Walk on FRET Networks -- Spatial photonic Ising machine with time/space division multiplexing -- Computing using Oscillatory Phenomena -- Sampling-like Dynamics of the Nonlinear Dynamical System Combined with Optimization -- Reservoir Computing Based on Iterative Function Systems -- Bridging the Gap between Reservoirs and Neural Networks -- Brain-Inspired Reservoir Computing Models. | |
506 | 0 | _aOpen Access | |
520 | _aThis open access book presents an overview of recent advances in photonic neural networks with spatiotemporal dynamics. The computing and implementation paradigms presented in this book are outcomes of interdisciplinary studies by collaborative researchers from the three fields of nonlinear mathematical science, information photonics, and integrated systems engineering. This book offers novel multidisciplinary viewpoints on photonic neural networks, illustrating recent advances in three types of computing methodologies: fluorescence energy transfer computing, spatial-photonic spin system, and photonic reservoir computing. The book consists of four parts: Part I introduces the backgrounds of optical computing and neural network dynamics; Part II presents fluorescence energy transfer computing, a novel computing technology based on nanoscale networks of fluorescent particles; Parts III and IV review the models and implementation of spatial-photonic spin systems andphotonic reservoir computing, respectively. These contents are beneficial to researchers in a broad range of fields, including information science, mathematical science, applied physics, and engineering, to better understand the novel computing concepts of photonic neural networks with spatiotemporal dynamics. | ||
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aNeural networks (Computer science) . | |
650 | 0 | _aNonlinear Optics. | |
650 | 1 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aMathematical Models of Cognitive Processes and Neural Networks. |
650 | 2 | 4 | _aNonlinear Optics. |
700 | 1 |
_aSuzuki, Hideyuki. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aTanida, Jun. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aHashimoto, Masanori. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789819950713 |
776 | 0 | 8 |
_iPrinted edition: _z9789819950737 |
776 | 0 | 8 |
_iPrinted edition: _z9789819950744 |
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-99-5072-0 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
912 | _aZDB-2-SOB | ||
942 | _cSPRINGER | ||
999 |
_c185733 _d185733 |