A control of real processes requires different approach to neural network learning. The presented modification of backpropagation learning algorithm changes a meaning of learning...
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Bayesian networks (BN) constitute a useful tool to model the joint distribution of a set of random variables of interest. To deal with the problem of learning sensible BN models fr...
This paper proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA)...
In this paper the popular PD controller of robot manipulator is modified. RBF neural networks are used to compensate the gravity and fi-iction. No exact knowledge of the robot dyn...