000			02885nam a22004455i 4500
001			978-3-662-43764-3
003			DE-He213
005			20200421111155.0
007			cr nn 008mamaa
008			140827s2015 gw | s |||| 0|eng d
020			_a9783662437643 _9978-3-662-43764-3
024	7		_a10.1007/978-3-662-43764-3 _2doi
050		4	_aQ342
072		7	_aUYQ _2bicssc
072		7	_aCOM004000 _2bisacsh
082	0	4	_a006.3 _223
100	1		_aRigatos, Gerasimos G. _eauthor.
245	1	0	_aAdvanced Models of Neural Networks _h[electronic resource] : _bNonlinear Dynamics and Stochasticity in Biological Neurons / _cby Gerasimos G. Rigatos.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2015.
300			_aXXIII, 275 p. 135 illus., 91 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aModelling Biological Neurons in Terms of Electrical Circuits -- Systems Theory for the Analysis of Biological Neuron Dynamics -- Bifurcations and Limit Cycles in Models of Biological Systems -- Oscillatory Dynamics in Biological Neurons -- Synchronization of Circadian Neurons and Protein Synthesis Control -- Wave Dynamics in the Transmission of Neural Signals -- Stochastic Models of Biological Neuron Dynamics -- Synchronization of Stochastic Neural Oscillators Using Lyapunov Methods -- Synchronization of Chaotic and Stochastic Neurons Using Differential Flatness Theory -- Attractors in Associative Memories with Stochastic Weights -- Spectral Analysis of Neural Models with Stochastic Weights -- Neural Networks Based on the Eigenstates of the Quantum Harmonic Oscillator -- Quantum Control and Manipulation of Systems and Processes at Molecular Scale -- References -- Index.
520			_aThis book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory. It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory.
650		0	_aEngineering.
650		0	_aArtificial intelligence.
650		0	_aComputational intelligence.
650	1	4	_aEngineering.
650	2	4	_aComputational Intelligence.
650	2	4	_aArtificial Intelligence (incl. Robotics).
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783662437636
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-662-43764-3
912			_aZDB-2-ENG
942			_cEBK
999			_c53452 _d53452