In this paper, a new approach based on Artificial Neural Network for data compression is presented. ANN (Artificial Neural Network) is playing a vital role to do complex works like face recognition, pattern recognition, currency recognition, compression, decompression etc. Artificial Neural networks have the potential to extend data compression algorithms beyond the character level n-gram model...

in wireless sensor networks, optimal consumptionof energy and having maximum life time are important factors. in this article attempt has been made to send the data packets with particular reliability from the beginning based on aodv protocol. in this way two new fields add to the routing packets and during routing and discovering of new routes, the lowest remained energy of nodes and route tra...

Image denoising techniques are essential to reducing noise levels and enhancing diagnosis reliability in low-dose computed tomography (CT). Machine learning based denoising methods have shown great potential in removing the complex and spatial-variant noises in CT images. However, some residue artifacts would appear in the denoised image due to complexity of noises. A cascaded training network ...

A recurrent neural net is described that learns a set of patterns {ξ µ } in the presence of noise. The learning rule is of a Hebbian type, and, if noise would be absent during the learning process, the resulting final values of the weights w ij would correspond to the pseudo-inverse solution of the fixed point equation in question. For a non-vanishing noise parameter, an explicit expression for...

premature ventricular contraction (pvc) is one of the common cardiac arrhythmias. the occurrence of pvc is dangerous in people who have recently undergone heart. a pvc beat can easily be diagnosed by a doctor based on the shape of the electrocardiogram signal. but in automatic detection, extracting several important features from each beat is required. in this paper, a method for automatic dete...

community detection is a task of fundamental importance in social network analysis. community structures enable us to discover the hidden interactions among the network entities and summarize the network information that can be applied in many applied domains such as bioinformatics, finance, e-commerce and forensic science. there exist a variety of methods for community detection based on diffe...

a novel algorithm for the fast detection of hubs in chemical networks is presented. thealgorithm identifies a set of nodes in the network as most significant, aimed to be the mosteffective points of distribution for fast, widespread coverage throughout the system. we showthat our hubs have in general greater closeness centrality and betweenness centrality thanvertices with maximal degree, while...