000 02772cam a2200469 i 4500
999 _c200425768
_d43691
001 200425768
003 TR-AnTOB
005 20231017170100.0
007 ta
008 231017t20152015nyua 000 0 eng
010 _a 2015945597
020 _a9783319198651
_q(hardback)
035 _a(TR-AnTOB)200425768
040 _aDLC
_beng
_erda
_cDLC
_dDLC
_dTR-AnTOB
041 0 _aeng
050 0 4 _aQA76.87
_b.K3743 2015
090 _aQA76.87
_b.K3743 2015
100 1 _aKashchenko, Serguey
_eauthor
_9144045
245 1 0 _aModels of wave memory /
_cSerguey Kashchenko.
264 1 _aNew York, NY :
_bSpringer Berlin Heidelberg,
_c2015.
264 4 _c©2015
300 _axxviii, 239 pages :
_billustrations ;
_c24 cm
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
490 0 _aLecture Notes in Morphogenesis,
_x2195-1934
500 _aSeries editor: Alessandro Sarti.
504 _aBIB
505 0 _aModel of single neuron -- Model of the interaction of neurons -- Model of wave propagations in the ring neural structure with chemical synapsis -- Model of self-organization of oscillations in the ring system of homogeneous neural modules -- Model of adaptation of neural ensembles -- Model of the neural system, synchronizing the wave packets -- Model of the neural system with diffusive interaction of elements -- Pseudo correlative dimension of the electroencephalogram and its volume amount of short term memory of the human -- Estimates of differences of evoked potentials.
520 _aThis monograph examines in detail models of neural systems described by delay-differential equations. Each element of the medium (neuron) is an oscillator that generates, in standalone mode, short impulses also known as spikes. The book discusses models of synaptic interaction between neurons, which lead to complex oscillatory modes in the system. In addition, it presents a solution to the problem of choosing the parameters of interaction in order to obtain attractors with predetermined structure. These attractors are represented as images encoded in the form of autowaves (wave memory). The target audience primarily comprises researchers and experts in the field, but it will also be beneficial for graduate students.
650 0 _aNeural networks (Computer science)
_9737
650 0 _aNeurosciences
_999921
650 0 _aStatistical physics
_9678
650 0 _aSystem theory
_9229
650 0 _aComputational complexity
_91359
653 0 _aMathematical Models of Cognitive Processes and Neural Networks
653 0 _aApplications of Nonlinear Dynamics and Chaos Theory
653 0 _aComplex Systems
653 0 _aComplexity
942 _2lcc
_cBK