In this paper, we consider a learning strategy that allows one to transmit information between two coupled phase oscillator systems (called teaching and learning systems) via frequency adaptation. The dynamics of these systems can be modeled with reference to a number of partially synchronized cluster states and transitions between them. Forcing the teaching system by steady but spatially nonho...

A new implementation of an autonomous hysteresis chaotic circuit using only two primitive cellular neural networks (CNN) cells is presented. Both computer simulations and laboratory measurements have confirmed the chaotic behavior and show the existence of the double scroll attractor. Key-Words: CNN, chaotic circuits, chaos, attractor, bifurcation, oscillator.

We suggest a method for suppression of synchrony in a globally coupled oscillator network, based on the time-delayed feedback via the mean field. Having in mind possible applications for suppression of pathological rhythms in neural ensembles, we present numerical results for different models of coupled bursting neurons. A theory is developed based on the consideration of the synchronization tr...

This paper presents a novel neural oscillator model that is inspired by biological oscillation models and is easily implemented in subthreshold analog CMOS VLSI. The proposed model uses local coupling among neuron units. Synchrony and information propagation are demonstrated in chains and rings of the oscillators.

Real-time cellular imaging of gene expression has revealed that fibroblasts contain a robust, self-sustained and cell-autonomous circadian oscillator, with a range of properties that both overlap and contrast with those of the neural clock of the suprachiasmatic nuclei.

This paper presents an automatic coding scheme for representing the output layer of a neural network. Compared t o local representation where the number of output unit is p , the number of output unit required for the proposed representation is close to logp. The output of seven different printers were used for evaluating the performance of the system. The proposed automatic representation gave...

Dynamic motion taking advantage of inertia with a flexible-joint robot is useful for energy efficiency and rapid motions. However, it is difficult to control flexible joints considering the complexity of their dynamics. To overcome the problem in past studies, oscillator [1], attractor [2], and search tree [3] methods have been explored. Attractors and oscillators force trajectories to return t...

In this paper, a new analytical approach has been presented for solving strongly nonlinear oscillator problems. Iteration perturbation method leads us to high accurate solution. Two different high nonlinear examples are also presented to show the application and accuracy of the presented method. The results are compared with analytical methods and with the numerical solution using Runge-Kutta m...

In this paper, we will present a theory of representing symbolic inferences of first-order logic with neural networks. The approach transfers first-order logical formulas into a variablefree representation (in a topos) that can be used to generate homogeneous equations functioning as input data for a neural network. An evaluation of the results will be presented and some cognitive implications ...