Nonlinear Dynamics, Quasi-Periodic Summation, Self-Oscillating Processes, and Information Coding in Selective Spiking Neural Networks

Abstract

Nonlinear dynamics, physical processes, and information processing in selective spiking neurons are investigated. Summation of pulse inputs are considered on the basis of the theory of quasi-periodic functions and nonlinear transformation via relaxation of the self-oscillating system of a neuron. A way of encoding input information is also considered in which the information unit is a pulse sequence, and the intensity of the input signal is encoded by a synchronous change in the frequency of the pulse sequences.