Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
It is well known that traditional educational techniques can be complemented by simulation to achieve a more effective learning experience. One would expect the same phenomenon to...
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
: This paper addresses the problem of designing an output error feedback tracking control for single-input, single-output, minimum phase, observable linear systems. The reference o...