The backward Viterbi beam search has not received enough attentions other than being used in the second pass. The reason is that the speech recognition society has long ignored the concept of dynamic complexities of a speech recognition task which can help us to determine whether we should operate Viterbi decoding in forward or backward direction. We use the U.S. street address entry task as on...

A functional equivalence of feed-forward networks has been proposed to reduce the search space of learning algorithms. A novel genetic learning algorithm for RBF networks and perceptrons with one hidden layer that makes use of this theoretical property is proposed. Experimental results show that our procedure outperforms the standard genetic learning. Key-Words: Feedforward neural networks, gen...

Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In recent years, many algorithms were proposed that perform very well in many situations. Nevertheless, when outlying values are present in the data, these methods often lead to wrong conclusio...

The paper proposes a segmentation procedure inspired to a robust LIDaR filtering data method recently introduced by the authors. The method is based on the application of a Simultaneous AutoRegressive (SAR) model for describing a trend surface and of an iterative Forward Search (FS) algorithm to detect clusters of non-stationary data. The procedure consists in an automatic process to identify r...

In this article, we provide a splitting method for solving monotone inclusions in real Hilbert space involving four operators: maximally monotone, monotone-Lipschitzian, cocoercive, and monotone-continuous operator. The proposed takes advantage of the intrinsic properties each operator, generalizing forward–backward–half-forward Tseng’s algorithm with line search. At iteration, our defines step...