Simulation performance versus stochasticity in large-scale cellular automata models
Due to a growing interest in chemical and biological phenomena, simulation of reaction-diffusion processes on micro-level becomes urgently wanted. Asynchronous cellular automata are promising mathematical models to be used as a base for creating computer simulation systems, which gives reason for the investigation of their capability. In particular, since the...
Location problems in renewable sensor networks with wireless energy transfer
The area of wireless sensor networks (WSNs) has recently received a lot of attention. Nevertheless, the major problem is the finite electrical batteries in sensors, which prevents the wide use of WSNs. However, technologies of the wireless energy transfer may be applied to solve energy problems in WSNs with the...
Geographical information system "The Earth's natural disasters Database" (ENDDB) as a tool for studying complex geotectonic structures
The software of geographical information system for studying the Earth's natural disasters (GIS-ENDDB), focused on the research into the cause- and-effect relations of catastrophic events in the history of our planet, contains data on seismic activity of the Earth, heat ows, detailed relief, and anomalies of the gravitational field as...
An associative version of the Ramalingam decremental algorithm for the dynamic all-pairs shortest-path problem
This paper proposes an efficient parallel representation of the Ramalingam algorithm for the dynamic update of the all-pairs shortest paths of a directed weighted graph after deleting an edge. To this end, a model of associative parallel systems with vertical processing (the STAR-machine) is used. The associative version is given...
Implementation of the STAR-machine on GPU
In this paper, we present the simulation of an abstract model of SIMD type with vertical data processing (the STAR-machine) on GPU with CUDA framework. There is a number of algorithms developed for the STAR-machine. The research conducted recently shows that such a model is extremely efficient when used to...
Regression analysis of text ranking algorithms by neural networks
Neural network models for the analysis of the document ranking algorithms are proposed. The models use the Kohonen neural network and a multilayer perceptron. These models were verified using test data, and their application features were revealed depending on the input data.
The memristor crossbar-based WTA neural network
The problems of programming memristor arrays (memristor crossbars) are considered. An estimate for the pulse width to set the desired memristor resistance (memristance) value is obtained. The implementation of the Winner-Take-All (WTA) neural network on the memristor crossbar and the NMOS transistors for binary images recognition is proposed. The proposed...