000			02558nam a2200349 i 4500
999			_c401630 _d401630
001			401630
003			ES-MaUEC
005			20240520100442.0
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007			cr nn 008mamaa
008			230919s2024 sz | fo |||| 0|eng d
020			_a9783031367052
024	7		_a10.1007/978-3-031-36705-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.87 _b2024 EB
245	0	0	_aBio-Inspired Information Pathways : _bFrom Neuroscience to Neurotronics _cedited by Martin Ziegler, Thomas Mussenbrock, Hermann Kohlstedt
250			_a1st ed. 2024
264		1	_aCham _bSpringer International Publishing _c2024
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aSpringer Series on Bio- and Neurosystems _x2520-8543 _v16
505	0		_aMatter & Mind Matter -- Neuromorphic circuits with redox-based memristive devices -- Redox-based bi-layer oxide metal memristive devices -- MemFlash - Floating Gate Transistors as Memristors -- Critical discussion of ex situ and in situ TEM measurements of memristive devices -- Modeling and Simulation of of Silver-based Filamentary Memristive Devices -- Bio-inspired, neuromorphic acoustic sensing.
506	0		_aOpen Access
520			_aThis open access book offers a timely and comprehensive review of the field of neurotronics. Gathering cutting-edge contributions from neuroscientists, biologists, psychologists, as well as physicists, microelectronics engineers and information scientists, it gives extensive information on fundamental information pathways in selected nervous systems. It also highlights their relevance as building blocks for novel computing architectures, such as bio-inspired electronic devices, neuromorphic architectures, memristive devices, adaptive sensors and emergent, pulsed-coupled oscillatory networks. All in all, this book offers a unique bridge between fundamental research in neuroscience, neural information processing, nonlinear dynamics, and self-organization, and advanced practical applications concerning the fabrication of hardware-oriented computing.
988			_aSpringer_Engineering_2024
650		7	_2embne _9678664 _aRedes neuronales artificiales
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-36705-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2024 _dz _eb _zSI