Press "Enter" to skip to content

Advanced Models of Neural Networks: Nonlinear Dynamics and by Gerasimos G. Rigatos PDF

By Gerasimos G. Rigatos

ISBN-10: 3662437635

ISBN-13: 9783662437636

ISBN-10: 3662437643

ISBN-13: 9783662437643

This booklet presents a whole learn on neural constructions displaying nonlinear and stochastic dynamics, elaborating on neural dynamics by way of introducing complicated types of neural networks. It overviews the most findings within the modelling of neural dynamics when it comes to electric circuits and examines their balance homes with using dynamical platforms concept.

It is acceptable for researchers and postgraduate scholars engaged with neural networks and dynamical structures theory.

Show description

Read or Download Advanced Models of Neural Networks: Nonlinear Dynamics and Stochasticity in Biological Neurons PDF

Best intelligence & semantics books

Singularity Theory and Its Applications: Warwick 1989: by M. Robert, I. Stewart PDF

A workshop on Singularities, Bifuraction and Dynamics used to be held at Warwick in July 1989, as a part of a year-long symposium on Singularity thought and its purposes. The court cases fall into halves: quantity I normally on connections with algebraic geometry and quantity II on connections with dynamical platforms concept, bifurcation thought and functions within the sciences.

Problem-Solving Methods: Understanding, Description, by Dieter Fensel PDF

This ebook offers a idea, a proper language, and a realistic technique for the specification, use, and reuse of problem-solving tools. The framework built via the writer characterizes knowledge-based platforms as a specific kind of software program structure the place the functions are constructed via integrating wide-spread activity requisites, challenge fixing tools, and area types: this method turns wisdom engineering right into a software program engineering self-discipline.

Read e-book online Participating in explanatory dialogues : interpreting and PDF

Whereas a lot has been written concerning the components of textual content new release, textual content making plans, discourse modeling, and consumer modeling, Johanna Moore's e-book is likely one of the first to take on modeling the complicated dynamics of explanatory dialogues. It describes an explanation-planning structure that permits a computational approach to take part in an interactive discussion with its clients, concentrating on the data buildings approach needs to construct on the way to complicated or make clear past utterances, or to reply to follow-up questions within the context of an ongoing discussion.

Additional info for Advanced Models of Neural Networks: Nonlinear Dynamics and Stochasticity in Biological Neurons

Sample text

11) where u D E. Additionally, from Eq. 12) By replacing Eqs. 13) From Eqs. 17) Example 3. Spring-mass system (Fig. 3). 1 Characteristics of the Dynamics of Nonlinear Systems 31 Fig. x1 ; x2 /. x1 ; x2 / have a constant slope. x/ D c is drawn in the x1 x2 plane and along this curve one also draws small linear segments of length c. x/ D c is known as isocline. x1 ; x2 /. Example 1. 30) For different values of c one has the following isoclines diagram depicted in Fig. 4. 2 Computation of Isoclines 33 Fig.

V@x D 0. x; t /, in different parts of the dendrites (Fig. 11). For each smaller part in the dendrite that is characterized by spatially uniform potential, the major parameters are: the cylinder’s radius ˛i , the length Li , the membrane’s potential Vi , the capacitance (normalized per unit of surface) ci , and the resistance of the membrane (normalized per unit of surface) rLi . It is assumed that in each compartment there is an electrode to which external current Ielectrode is applied. 7 Modelling Dendrites in Terms of Electrical Circuits 17 Fig.

Some terminology associated with fixed points is as follows. A fixed point for the system of Eq. 50) is called hyperbolic if none of the eigenvalues of matrix A has zero real part. A hyperbolic fixed point is called a saddle if some of the eigenvalues of matrix A have real parts greater than zero and the rest of the eigenvalues have real parts less than zero. If all of the eigenvalues have negative real parts, then the hyperbolic fixed point is called a stable node or sink. If all of the eigenvalues have positive real parts, then the hyperbolic fixed point is called an unstable node or source.

Download PDF sample

Advanced Models of Neural Networks: Nonlinear Dynamics and Stochasticity in Biological Neurons by Gerasimos G. Rigatos

by Robert

Rated 4.94 of 5 – based on 17 votes