In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
In this paper, we propose a powerful symmetric radial basis function (RBF) classifier for nonlinear detection in the so-called "overloaded" multiple-antenna-aided communi...
Sheng Chen, Andreas Wolfgang, Chris J. Harris, Laj...
In this paper, it is found that the weights of a perceptron are bounded for all initial weights if there exists a nonempty set of initial weights that the weights of the perceptron...
Charlotte Yuk-Fan Ho, Bingo Wing-Kuen Ling, Hak-Ke...
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
This paper presents a pattern classification system in which feature extraction and classifier learning are simultaneously carried out not only online but also in one pass where tr...
Abstract-- A major drawback of artificial neural networks (ANNs) is their black-box character. This is especially true for recurrent neural networks (RNNs) because of their intrica...
Abstract--Hyperspectral imagery affords researchers all discriminating details needed for fine delineation of many material classes. This delineation is essential for scientific re...
Separation of speech mixtures, often referred to as the cocktail party problem, has been studied for decades. In many source separation tasks, the separation method is limited by t...
Michael Syskind Pedersen, DeLiang Wang, Jan Larsen...
An experimental study on two decision issues for wrapper feature selection (FS) with multilayer perceptrons and the sequential backward selection (SBS) procedure is presented. The ...