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Models of Wave Memory: Lecture Notes in Morphogenesis

Autor Serguey Kashchenko
en Limba Engleză Hardback – 15 oct 2015
This 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.
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Specificații

ISBN-13: 9783319198651
ISBN-10: 3319198653
Pagini: 200
Ilustrații: XXVIII, 239 p.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.55 kg
Ediția:1st ed. 2015
Editura: Springer International Publishing
Colecția Springer
Seria Lecture Notes in Morphogenesis

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Model 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.

Textul de pe ultima copertă

This 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.

Caracteristici

Provides valuable content for specialists in oscillatory neural networks Presents a solution to the problem of image comparison and attractor identification Written by experts in the field Includes supplementary material: sn.pub/extras