Photonic reservoir computing : optical recurrent neural networks
Material type: TextPublication details: Berlin Gruyter, De 2019Description: xii, 264 pISBN: 9783110582000Subject(s): Quantum computing | Optical data processing | Optoelectronic devicesDDC classification: 621.367 Summary: Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.Item type | Current library | Call number | Status | Date due | Barcode |
---|---|---|---|---|---|
BK | Stack | 621.367 PHO (Browse shelf (Opens below)) | Available | 54412 |
Browsing Kannur University Central Library shelves, Shelving location: Stack Close shelf browser (Hides shelf browser)
621.367 GON/D Digital image processing / | 621.367 JEN/I Introductory digital image processing | 621.367 OGO/P Practical algorithms for image analysis : | 621.367 PHO Photonic reservoir computing : optical recurrent neural networks | 621.367 RUS/I The image processing handbook / | 621.367 SHA Digital Image Processing | 621.3678 BHA/F Fundamentals of remote sensing |
Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.
There are no comments on this title.