Journal:Informatica
Volume 9, Issue 2 (1998), pp. 141–160
Abstract
The nonlinearities play a crucial role in the brain processes. They take place in neuronal system elements: synapses, dendrite membranes, soma of neurons, axons. It is established that the soma nonlinearity, which is of sigmoidal shape, is not so strong as compared with the electric current-voltage relation of a dendrite membrane. The relation is N-shaped with two stable and one unstable points. In dynamics, this leads to the appearance of a switch wave or formation of some logic functions. We present some artificial logic circuits based on an electrical analogy of dendritic membrane characteristics in static and dynamic cases. The nonlinear cable theory and the numerical simulation were used. Basing on the logic circuit construction proposed, we suppose that the dendritic membrane processes are able not only to gather and transfer information but also to transform and classify knowledge.
The theoretical substantiation and numerical experiments are only the first step forward to the proving of neuronal dendritic logic constructions. Of course, extensive neurophysiological tests are necessary to discover the final mechanism of neuronal computing in the human brain.
Journal:Informatica
Volume 7, Issue 4 (1996), pp. 431–454
Abstract
Adaptive Control Distributed Parameter Systems (ACDPS) with adaptive learning algorithms based on orthogonal neural network methodology are presented in this paper. We discuss a modification of orthogonal least squares learning to find appropriate efficient algorithms for solution of ACDPS problems. A two times problem linked with the real time of plant control dynamic processes and the learning time for adjustment of parameters in adaptive control of unknown distributed systems is discussed.
The simulation results demonstrate that the orthogonal learning algorithms on a neural network concept allow to find perfectly tracked output control distributed parameters in ACDPS and have rather a good perspective in the development of generalised ACDSP theory and practice in the future.
Journal:Informatica
Volume 4, Issues 1-2 (1993), pp. 140–147
Abstract
A stochastic discrete neuronetwork is defined. In the investigation of discrete neuronetworks probability methods are applied – a weak convergence of probability measures. Limit theorems (the strong law of large number and normal law) are proved for the stream of signals, going out of neurons.
Journal:Informatica
Volume 3, Issue 4 (1992), pp. 469–473
Abstract
The binary logic functions “excitation and/or noninhibition” and “excitation and noninhibition” are realized by the model of a nonlinear stationary dendritic branch. The neuron with such dendrites is a complex logic system performing a great member of elementary logic operations.
Journal:Informatica
Volume 3, Issue 3 (1992), pp. 385–392
Abstract
Binary logic functions ‘AND’ and ‘OR’ of negations are realized by a dendritic branch with nonlinear current-voltage characteristic of membrane. The neuron with such dendrites is a complex logic system performing a great number of elementary logic operations.
Journal:Informatica
Volume 2, Issue 3 (1991), pp. 403–413
Abstract
The binary logic functions “AND” and “OR” are realized by the model of a nonlinear stationary dendritic branch. The neuron with such dendrites is a complex logic system performing a great number of elementary logic operations.
Journal:Informatica
Volume 2, Issue 2 (1991), pp. 221–232
Abstract
The principles of a neural network environmental model are proposed. The principles are universal and can use different neural network architectures. Such a model is self-organizing, it can operate in both regimes with and without a teacher. It codes information about objects, their features, the actions operating in an environment, analyzes concrete situations. There are functions for making an action plan, for action control. The goal of the model is given from an external site. The model has more than sixteen active regimes. The neural network environmental model is fulfilled in software and hardware tools.