Some properties of asymmetric Hopfield neural networks with finite time of transition between states

There were implemented samples of asymmetric Hopfield neural networks which have finite time of transition from one state to another. It was shown that in such systems, various oscillation modes could occur. It was revealed that the oscillation of the output signal of certain neuron could be treated as extra logical variable, which describes the state of the neuron. Asymmetric Hopfield neural networks are described in terms of ternary logic. Such logic may be employed in image recognition procedure.

A Circuit Simulator Applicable to Fault Simulation

In view of the demand of circuit fault simulation analysis, a novel circuit simulator for fault simulation was designed to overcome the shortcomings of traditional circuit simulation tools in fault simulation. The principles and method of this simulator were proposed, which focus on the realization of the basic functions and weakens detail characteristics. Based on the method, the components simulation models and fault models with the combination of the numerical variable with logical variable were built. Moreover, the implementation algorithm and simulation flow were introduced to show how to simulate a circuit based on this simulation model. At last, an example was simulated to verify the feasibility of this method. It is shown that, this circuit simulator will become a valuable tool for the circuit fault simulation and analysis.

COLLISION-BASED COMPUTING IN BIOPOLYMERS AND THEIR AUTOMATA MODELS

In collision-based computing, quanta of information are represented by autonomous mobile signals. The signals travel in a uniform architectureless medium. They collide to each other. Assuming the presence or abscence of a signal represent truth or falsity values of logical variable, we can consider logical functions are calculated at the sites of signals' collision. Physically, the signals are localized compact disturbances of medium's characteristics. In this paper, we extensively exploit results published in Refs. 1–7. We consider three types of localizations: breathers in one-dimensional arrays of DNA molecules, excitons and groups of antialigned dipoles in two-dimensional arrays of Scheibe aggregates and microtubules respectively. Several forms of logical gates are extracted from published results on numerical simulation of breathers and excitons. In cellular automata models, we study interactions of the localizations with each other. We show what kinds of logical gates can be realized in such interactions. Parallels between physical and discrete automata models are provided.