There is increasing interest in quantum computing, because of its enormous computing potential. A small number of powerful quantum algorithms have been proposed to date; however, the development of new quantum algorithms for practical use remains essential. Parallel computing with a neural network has successfully realized certain unique functions such as learning and recognition; therefore, th...

Computation without stable states is a computing paradigm different from Turing’s and has been demonstrated for various types of simulated neural networks. This publication transfers this to a hardware implemented neural network. Results of a software implementation are reproduced showing that the performance peaks when the network exhibits dynamics at the edge of chaos. The liquid computing ap...

This paper deals the potential of parallel computing on graphics cards. In many applications we encounter time-consuming mathematical or general computing operations, which handle large amounts of data. One of these applications is artificial neural network. One solution to speed up such calculations is to get them done on a graphics card. Graphics cards with CUDA (Compute Unified Device Archit...

if both reference station (rs) and navigational device in differential global positioning system (dgps) receive signals from the same satellite, rs position components error (rpce) can be used to compensate for navigational device error. this research used hybrid method for rpce prediction which was collected by a low-cost gps receiver. it is a combination of genetic algorithm (ga) computing an...

the main aim of this paper is to find the optimum shape of arch dams subjected to multiple natural frequency constraints by using an efficient methodology. the optimization is carried out by charged system search algorithm and its enhanced version. computing the natural frequencies by finite element analysis (fea) during the optimization process is time consuming. in order to reduce the computa...