This paper presents a simple continuous analog hardware realization of the Random Neural Network (RNN) model. The proposed circuit uses the general principles resulting from the u...
Artificial neural networks (ANN), esp. multilayer perceptrons (MLP) have been widely used in pattern recognition and classification. Nevertheless, how to incorporate a priori know...
—This paper describes an approach to classification of noisy signals using a technique based on the fuzzy ARTMAP neural network (FAMNN). The proposed method is a modification of ...
Dimitrios Charalampidis, Michael Georgiopoulos, Ta...
—This study investigates the processing of sonar signals using neural networks for robust differentiation of commonly encountered features in indoor robot environments. The neura...
Abstract. Finite-state machines are the most pervasive models of computation, not only in theoretical computer science, but also in all of its applications to real-life problems, a...
This paper proposes the general paradigm to build Q'tron neural networks (NNs) for visual cryptography. Given a visual encryption scheme, usually described using an access st...
One of the main research concern in neural networks is to find the appropriate network size in order to minimize the trade-off between overfitting and poor approximation. In this ...
Marques and Almeida [9] recently proposed a nonlinear data seperation technique based on the maximum entropy principle of Bell and Sejnowsky. The idea behind is a pattern repulsion...
Fabian J. Theis, Christoph Bauer, Carlos Garc&iacu...
It is presented in this paper a new approach to the problem of feature extraction. The approach is based on the edge detection, where a set of feature vectors is taken from the sou...
Roberto J. Rodrigues, Gizelle Kupac Vianna, Antoni...