In welded tubular joints, when the fatigue crack depth is less than 20% of chord wall thickness, the crack growing process is highly affected by weld geometry.&#10 Hence, T-butt solution and weld magnification factor (Mk) are applicable tools for evaluating the crack growth rate in this domain. In this research, the capability of Artificial Neural Network (ANN) for estimating the Mk of weld toe...

In welded tubular joints, when the fatigue crack depth is less than 20% of chord wall thickness, the crack growing process is highly affected by weld geometry. Hence, T-butt solution and weld magnification factor (Mk) are applicable tools for evaluating the crack growth rate in this domain. In this research, the capability of Artificial Neural Network (ANN) for estimating the Mk of weld toe c...

This paper discusses the development of a system for the automated real-time measurement of crystal size distributions during crystallisation. An optimised selection of the Daubechies wavelet coefficients is used as input to a Multi–Layer Perceptron artificial neural network to characterise the crystal scale lengths. This technique gives significant advantages over the sampling-based measuremen...

The purpose of train detection systems is to check that related track section clear vehicles before a may be authorized pass through railroad. the important task for ensuring safety traffic. Multi-layer Perceptron classifier, which consists feedforward neural networks constructed multiple layers interconnected artificial neurons, proved effective trainset class classification in this study. Usi...

This paper deals with a novel feature extraction method for text dependent speaker recognition. Four female speakers were used to create a text –dependent database for Malayalam (one of the south Indian languages). Discrete Wavelet Transform was used for feature extraction and artificial neural network was used for machine intelligence. In this work we used emotional features for speaker recogn...

In this paper, we will consider the problem of classifying electroencephalogram (EEG) signals of normal subjects, and subjects suffering from psychiatric disorder, e.g., obsessive compulsive disorder, schizophrenia, using a class of artificial neural networks, viz., multi-layer perceptron. It is shown that the multilayer perceptron is capable of classifying unseen test EEG signals to a high deg...

Artificial Neural Network is widely used to learn data from systems for different types of applications. The capability of different types of Integrated Circuit (IC) based ANN structures also depends on the hardware backbone used for their implementation. In this work, Field Programmable Gate Array (FPGA) based Multilayer Perceptron Artificial Neural Network (MLP-ANN) neuron is developed. Exper...