Somesh Kumar

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Fuzzy control is a very successful way to transform the expert's knowledge of the type " if the velocity is big and the distance from the object is small, hit the brakes and decelerate as fast as possible " into an actual control. To apply this transformation one must: 1) choose fuzzy variables corresponding to words like " small " , " big " ; 2) choose(More)
We develop protocols for preparing a GHZ state and, in general, a pure multi-partite maximally entangled state in a distributed network with apriori quantum entanglement between agents using classical communication and local operations. We investigate and characterize the minimal combinatorics of the sharing of EPR pairs required amongst agents in a network(More)
BACKGROUND Postpartum intrauterine contraceptive devices (PPIUCD) are increasingly included in many national postpartum family planning (PPFP) programs, but satisfaction of women who have adopted PPIUCD and complication rates need further characterization. Our specific aims were to describe women who accepted PPIUCD, their experience and satisfaction with(More)
Function approximation is an instance of supervised learning which is one of the most studied topics in machine learning, artificial neural networks, pattern recognition, and statistical curve fitting. In principle, any of the methods studied in these fields can be used in reinforcement learning. Multi-layered feed-forward neural networks (MLFNN) have been(More)
The combination of evolutionary algorithms and ANN has been a recent interest in the field of research. Hopfield model is a type of recurrent neural network which has been widely studied for the purpose of associative memories. In the present work, this Hopfield Model of feedback neural networks has been studied with Monte Carlo adaptation learning rule and(More)