Echo state neural networks, which are a special case of recurrent neural networks, are studied from the viewpoint of their learning ability, with a goal to achieve their greater prediction ability. A standard training of these neural networks uses pseudoinverse matrix for one-step learning of weights from hidden to output neurons. Such learning was substituted by backpropagation of error learni...

A new neural network architecture is proposed and applied in classification of data from multiple sources. The new arclhitecture is called a consensual neural network and its relation to hierarchical and ensemble neural networks is discussed. The consenr;ual neural nebwork architecture is based on statistical consensus theory and invol.ves using non-linearly transformed input data. The input da...

A vector matrix real time backpropagation algorithm for recurrent neural networks that approximate multi-valued periodic functions," Received Unlike feedforward neural networks (FFNN) which can act as universal function ap-proximators, recursive, or recurrent, neural networks can act as universal approximators for multi-valued functions. In this paper, a real time recursive backpropagation (RTR...

Handoff decisions are usually signal strength based because of simplicity and effectiveness. Apart from the conventional techniques, such as threshold and hysteresis based schemes, recently many artificial intelligent techniques such as Fuzzy Logic, Artificial Neural Network (ANN) etc. are also used for taking handoff decision. In this paper, an Artificial Neural Network based handoff algorithm...

Neural Network is a computational paradigm that comprises several disciplines such as mathematics, statistic, biology and philosophy. Neural Network has been implemented in many applications; in software and even hardware. In most cases, Neural Network considered large amount of data, as it will be teach to learn or memorize the data as the knowledge. The learning mechanism for Neural Network i...

Face recognition is one of the biometric methods that is used to identify any given face image using the main features of this face. In this research, a face recognition system was suggested based on four Artificial Neural Network (ANN) models separately: feed forward backpropagation neural network (FFBPNN), cascade forward backpropagation neural network (CFBPNN), function fitting neural networ...

It is difficult to find out which is more effective and accurate method for stock rate prediction so that a buy or sell signal can be generated for given stocks. This paper presents a number of technical indicators and Back Propagation Neural Network to predict the stock price of the day. Stock rate prediction accuracy of different technical indicators and backpropagation neural network has bee...

In this paper we present a comparison between NeuroEvolution of Augmenting Typologies (NEAT) algorithm with Backpropagation Neural Network for the prediction of breast cancer. Machine learning algorithms could be used to enhance the performance of medical practitioners in the diagnosis of breast cancer. NEAT is a promising machine learning algorithm, which combines genetic algorithms and neural...