A mesh model is implemented on cellular neural networks. We devise a new energy function for the mesh model in the form of cellular neural network. By operating the parameters of the cellular neural networks, the mesh guided by this energy function will behave as in.

future increase of mobile communication subscribers will require a great capacity expansion of the cellular systems. in order to accommodate the increasing number of subscribers, the cell size will have to be much smaller than current size. therefore, it is predictable that the location updating and paging procedures will produce a major part of signaling traffic in these networks. this pape...

We present “Rules of Thumb” for efficient and simple parallelization of Cellular Neural Networks (CNNs). The rules result from the application and optimization of the simple but effective structural data parallel approach, which is based on the SPMD model. The process of parallelizing the algorithm employs HPF to generate an MPI-based program.

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

in this paper an application of cellular learning automata (cla) to vlsi placement is presented. the cla, which is introduced for the first time in this paper, is different from standard cellular learning automata in two respects. it has input and the cell neighborhood varies during the operation of cla. the proposed cla based algorithm for vlsi placement is tested on number of placement proble...