One of the major difficulties facing researchers using neural networks is the selection of the
proper size and topology of the networks. The problem is even more complex because often …

This paper proposes a novel artificial neural network called Parallel Layer Perceptron Fast
Learning Network (PLP-FLN). In PLP-FLN, a parallel single hidden layer feed-forward …

A committee of neural networks is the aggregation of two or more neural networks for
making overall predictions that are supposedly more accurate than those obtained by the …

Space-division multiplexing (SDM) techniques bring new approaches for various
applications in microwave photonic signal processing. In this work, an all-fiber …

This paper presents a new concept of a dual neural network which is hybrid of linear and
nonlinear network. This approach allows for solving the problem of Parity-3 with only one …

Artificial neural networks are usually applied to solve complex problems. In problems with
more complexity, by increasing the number of layers and neurons, it is possible to achieve …

This manuscript describes the design and numerical implementation of a novel composite
differential neural network aimed to estimate nonlinear uncertain systems. A differential …

Cancer genomics and precision medicine are growing fields of medicine to accomplish
better treatment for lethal diseases such as cancer. In the post genomics era, growing …

In this paper we present and analyze a modular implementation of the Multilayer Perceptron
(MLP) network in the view of the recent paradigm shift called the multicore era. The …

Very little time has been devoted to the application of Dual Neural Networks and advances
that they might produce by utilizing them for conversion between network architectures. By …