In this paper, a new hybrid adaptation model for cancer diagnosis has been developed. It combines transformational and hierarchical adaptation techniques with artificial neural ne...
A neural network model that can simulate the learning of some simple proportional analogies is presented. These analogies include, for example, (a) red-square:red-circle yellow-sq...
This paper studies the design and application of the neural network based adaptive control scheme for autonomous underwater vehicle's (AUV's) depth control system that i...
Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks in which the synaptic interactions are mediated via a nonlinear mechanism called shuntin...
— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...