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710	2		_aSpringerLink (Online service) _9106996
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003			ES-MaUEC
005			20230102113522.0
008			180517s2019 gw a o |||| 0|eng d
020			_a9783319901404
024	7		_a10.1007/978-3-319-90140-4 _2doi
040			_bspa _aES-MaUEC _cES-MaUEC
050		4	_aQP363 _b2019 EB
100	1		_aBielecki, Andrzej _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9671301
245	1	0	_aModels of Neurons and Perceptrons : _bSelected Problems and Challenges _cby Andrzej Bielecki.
264		1	_aCham _bSpringer International Publishing _c2019
300			_a1 recurso en línea (VI, 156 páginas) _b30 ilustraciones
347			_atext file _bPDF
490	0		_aStudies in Computational Intelligence _x1860-949X _v770
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aIntroduction -- Part I: Preliminaries -- Foundations of artificial neural networks -- Part II: Mathematical foundations -- General foundations -- Foundations of dynamical systems theory -- Part III: Mathematical models of the neuron -- Models of the whole neuron -- Models of parts of the neuron -- Part IV: Mathematical models of the perceptron -- General model of the perceptron -- Linear perceptrons -- Weakly nonlinear perceptrons -- Nonlinear perceptrons -- Concluding remarks and comments.
520	3		_aThis book describes models of the neuron and multilayer neural structures, with a particular focus on mathematical models. It also discusses electronic circuits used as models of the neuron and the synapse, and analyses the relations between the circuits and mathematical models in detail. The first part describes the biological foundations and provides a comprehensive overview of the artificial neural networks. The second part then presents mathematical foundations, reviewing elementary topics, as well as lesser-known problems such as topological conjugacy of dynamical systems and the shadowing property. The final two parts describe the models of the neuron, and the mathematical analysis of the properties of artificial multilayer neural networks. Combining biological, mathematical and electronic approaches, this multidisciplinary book it useful for the mathematicians interested in artificial neural networks and models of the neuron, for computer scientists interested in formal foundations of artificial neural networks, and for the biologists interested in mathematical and electronic models of neural structures and processes.
650		7	_aNeuronas _9144348 _2embne
776	0	8	_iPrinted edition: _z9783319901398
776	0	8	_iPrinted edition: _z9783319901411
776	0	8	_iPrinted edition: _z9783030079420
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-90140-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aPrimersemestre_2019_Robotics
998			_aSI _a_alco _a_vill _b11/2019 _cm _dz _ea _feng _ggw _h0