The conventional channel-optimized vector quantization (COVQ) is very powerful in the
protection of vector quantization (VQ) data over noisy channels. However, it suffers from the time …

In classical training methods for node open fault, we need to consider many potential faulty
networks. When the multinode fault situation is considered, the space of potential faulty …

This article aims at identifying significant factors influencing behavioural intention and
resistance of patients toward electronic health record sharing systems by using PLS-SEM. A …

This paper develops two neural network models, based on Lagrange programming neural
networks (LPNNs), for recovering sparse signals in compressive sampling. The first model is …

A distributed k-Winner-Take-All (kWTA) is presented in this paper. Its state-space model is
given by d dt x i ( t ) = - h ( x i ( t ) + u i ) - k n + β ∑ j ∈ N i ( x i ( t ) - x j ( t ) ) z i ( x i ( t ) ) = h ( x i …

In this paper, we investigate the attraction basin of the bidirectional associative memory (BAM)
model. The BAM is a two-layer heteroassociator that stores a prescribed set of bipolar …

Ant routing is a method for network routing in agent technology. Although its effectiveness
and efficiency have been demonstrated and reported in the literature, its properties have not …

… Additionally, the sum of these percentages should equal 1. A similar requirement for the two
… to attain the target sparsity level, resulting in the sum being not equal to 1. Furthermore, a …

In the use of the extended Kalman filter approach in training and pruning a feedforward neural
network, one usually encounters the problems of how to set the initial condition and how …

The single-layer perceptron, introduced by Rosenblatt in 1958, is one of the earliest and
simplest neural network models. However, it is incapable of classifying linearly inseparable …