東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Photonic neural networks with spatiotemporal dynamics = paradigms of computing and implementation /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Photonic neural networks with spatiotemporal dynamics/ edited by Hideyuki Suzuki, Jun Tanida, Masanori Hashimoto.
Reminder of title:	paradigms of computing and implementation /
other author:	Suzuki, Hideyuki.
Published:	Singapore :Springer Nature Singapore : : 2024.,
Description:	viii, 278 p. :ill., digital ;24 cm.
[NT 15003449]:	Revival 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.
Contained By:	Springer Nature eBook
Subject:	Neural networks (Computer science) -
Online resource:	https://doi.org/10.1007/978-981-99-5072-0
ISBN:	9789819950720

Photonic neural networks with spatiotemporal dynamics = paradigms of computing and implementation /
Photonic neural networks with spatiotemporal dynamicsparadigms of computing and implementation /[electronic resource] :edited by Hideyuki Suzuki, Jun Tanida, Masanori Hashimoto. - Singapore :Springer Nature Singapore :2024. - viii, 278 p. :ill., digital ;24 cm.

Revival 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.

Open access.

This 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 and photonic 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.

ISBN: 9789819950720

Standard No.: 10.1007/978-981-99-5072-0doiSubjects--Topical Terms:

532070
Neural networks (Computer science)

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

Photonic neural networks with spatiotemporal dynamics = paradigms of computing and implementation /
LDR:03058nmm a2200337 a 4500 001 2367505
003 DE-He213
005 20231016173736.0
006 m d
007 cr nn 008maaau
008 241127s2024 si s 0 eng d
020 $a 9789819950720 $q (electronic bk.)
020 $a 9789819950713 $q (paper)
024 7 $a 10.1007/978-981-99-5072-0 $2 doi
035 $a 978-981-99-5072-0
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.87
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.32 $2 23
090 $a QA76.87 $b .P575 2024
245 0 0 $a Photonic neural networks with spatiotemporal dynamics $h [electronic resource] : $b paradigms of computing and implementation / $c edited by Hideyuki Suzuki, Jun Tanida, Masanori Hashimoto.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2024.
300 $a viii, 278 p. : $b ill., digital ; $c 24 cm.
505 0 $a Revival 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 $a Open access.
520 $a This 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 and photonic 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 $a Neural networks (Computer science) $3 532070
650 1 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Mathematical Models of Cognitive Processes and Neural Networks. $3 1619875
650 2 4 $a Nonlinear Optics. $3 3538901
700 1 $a Suzuki, Hideyuki. $3 2133801
700 1 $a Tanida, Jun. $3 3710660
700 1 $a Hashimoto, Masanori. $3 3710661
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-99-5072-0
950 $a Computer Science (SpringerNature-11645)