Titlebook: Artificial Intelligence and Soft Computing; 14th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

破裂

Outmoded

自愛(ài)

I. Vernaleken,F. Schneider,W. Nieblingt structure and dependences is used to estimate the time of TRACO transformations. The training of a Feed-Forward Neural Network is used to make a decision about transformation time. Experiments with various NAS Parallel Benchmarks show promise for the use of neural networks in automatic code parallelization and optimization.

mortuary

LUT

Microarray , Gene Data Clustering by Means of Generalized Self-organizing Neural Networks with Evolv to complex cluster-analysis problems including, in particular, the sample-based and gene-based clusterings of microarray . gene data set. Our approach works in a fully unsupervised way, i.e., without the necessity to predefine the number of clusters and using unlabelled data. It is particularly imp

Horizon

Ballad

thwart

現(xiàn)代

Extensions of Hopfield Neural Networks for Solving of Stereo-Matching Problemel architectures are examined: Hybrid-Maximum Neural Network and Self Correcting Neural Network.Energy functions that are crucial for the network performance and working algorithm are also presented.All considered structures are tested to compare their performance features. Two of them are particula

muscle-fibers

Molecular Approach to Hopfield Neural Network. This novel approach uses magnetic molecules homogenously distributed in mesoporous silica matrix, which forms a base for a converting unit, an equivalent of a neuron in the Hopfield network. Converting units interact with each other via a fully controlled magnetic fields, which corresponds to weig