Abraham Miliotis

Chaogates: Morphing logic gates that exploit dynamical patterns

Chaotic systems can yield a wide variety of patterns. Here we use this feature to generate all possible fundamental logic gate functions. This forms the basis of the design of a dynamical computing device, a chaogate, that can be rapidly morphed to become any desired logic gate. Here we review the basic concepts underlying this and present an extension of the formalism to include asymmetric logic functions.

EXPLOITING NONLINEAR DYNAMICS TO STORE AND PROCESS INFORMATION

By applying nonlinear dynamics to the dense storage of information, we demonstrate how a single nonlinear dynamical element can store M items, where M is variable and can be large. This provides the capability for naturally storing data in different bases or in different alphabets and can be used to implement multilevel logic. Further we show how this method of storing information can serve as a preprocessing tool for (exact or inexact) pattern matching searches. Since our scheme involves just a single procedural step, it is naturally set up for parallel implementation and can be realized with hardware currently employed for chaos-based computing architectures.

Exploiting Nonlinear Dynamics to Search for the Existence of Matches in a Database

We propose a method that uses nonlinear dynamics to address the task of determining the existence of a specific item in an unsorted arbitrarily large database. The scheme involves a single global operation applied simultaneously to all elements of the database and a single global monitoring threshold for verification of existence. We also show how this global threshold can be altered for identification of the existence of items with characteristics close to the searched one

Synchrony with shunting inhibition

J Crayton Pruitt Department of Biomedical Engineering,University of Florida, Gainesville, FL 32611(Dated: January 30, 2009)Spike time response curves (STRC’s) are used to study the influence of synaptic stimuli on thefiring times of a neuron oscillator without the assumption of weak coupling. They allow us toapproximate the dynamics of synchronous state in networks of neurons through a discrete map,which can then be used to predict the stability of patterns of synchrony in the network. Generaltheory for taking into account the contribution from higher order STRC terms, resulting fromperturbations caused by synaptic stimuli lasting for more than one firing cycle of a neuron, in theapproximation of the discrete map is still lacking. Here we present a general theory to account forhigher order STRC corrections in the approximation of discrete map to determine the domain of 1:1phase locked state in a network of two interacting neurons. We test the ability of this discrete mapto predict the domain of 1:1 phase locked state in a network of two neurons interacting through ashunting synapse.