Produktbild: Photonic Neural Networks with Spatiotemporal Dynamics

Photonic Neural Networks with Spatiotemporal Dynamics Paradigms of Computing and Implementation

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

17.10.2023

Herausgeber

Hideyuki Suzuki + weitere

Verlag

Springer Singapore

Seitenzahl

278

Maße (L/B/H)

23.5/15.5/1.5 cm

Gewicht

493 g

Auflage

1st edition 2024

Sprache

Englisch

ISBN

978-981-9950-74-4

Beschreibung

Portrait

Hideyuki Suzuki received the B.S. degree in mathematics, and the M.E. and Ph.D. degrees in mathematical engineering from the University of Tokyo in 1996, 1998 and 2001, respectively. He is currently a Professor in the Graduate School of Information Science and Technology at Osaka University. His current research interests include nonlinear dynamics and its applications.

Jun Tanida received the B.E., M.E., and Ph.D. degrees in applied physics from Osaka University in 1981, 1983, and 1986, respectively. He is currently a Professor in the Graduate School of Information Science and Technology at Osaka University. His current research interests include information photonics, computational imaging, and photonic DNA computing.

Masanori Hashimoto received the B.E., M.E., and Ph.D. degrees in communications and computer engineering from Kyoto University in 1997, 1999, and 2001, respectively. He is currently a Professor in the Department of Informatics at Kyoto University. His current research interests include the design for manufacturability and reliability, soft error characterization, timing and power integrity analysis, reconfigurable computing, and low-power circuit design.

 



Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

17.10.2023

Herausgeber

Verlag

Springer Singapore

Seitenzahl

278

Maße (L/B/H)

23.5/15.5/1.5 cm

Gewicht

493 g

Auflage

1st edition 2024

Sprache

Englisch

ISBN

978-981-9950-74-4

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Photonic Neural Networks with Spatiotemporal Dynamics
  • 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.