FIR neural networks are feedforward neural networks with regular scalar synapses replaced by linear finite impulse response filters. This paper introduces the Second Order Temporal Backpropagation algorithm which enables the exact calculation of the second order error derivatives for a FIR neural network. This method is based on the error gradient calculation method first proposed by Wan and re...

Face recognition is a system that identifies human faces from an image database or from a video frame . The paper presents a literature review on face recognition approaches. It then explains two different algorithms for feature extraction which are Principal Component Analysis and Fisher Faces algorithm. It also explains how images can be recognized using a Backpropagation algorithm on a Feedf...

This paper evaluates the usefulness of neural networks in GDP forecasting. It is focused on comparing a neural network model trained with genetic algorithm (GANN) to a backpropagation neural network model, both used to forecast the GDP of Albania. Its forecasting is of particular importance in decision-making issues in the field of economy. The conclusion is that the GANN model achieves higher ...

The backpropagation artificial neural network (ANN) is a well-known and widely applied mathematical model for remote sensing applications for pattern recognition, approximation and mapping of non-linear functions and time-series prediction. The backpropagation ANN algorithm is underpinned by a gradient descent algorithm that is used to modify the network weights to maximise performance, using s...

Learning process is essential for good performance when a neural network is applied to a practical application. The backpropagation algorithm [1] is a well-known learning method widely used in most neural networks. However, since the backpropagation algorithm is time-consuming, much research have been done to speed up the process. The block backpropagation algorithm, which seems to be more effi...

This study compares the predictive performance of three neural network methods, namely the Learning Vector Quantization, the Radial Basis Function, and the Feedforward network that uses the conjugate gradient optimization algorithm, with the performance of the logistic regression and the backpropagation algorithm. All these methods are applied to a dataset of 139 matched-pairs of bankrupt and n...

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...