In this paper, a new Multi-Layer Perceptron Neural Network (MLP NN) classifier is proposed for classifying sonar targets and non-targets from the acoustic backscattered signals. Besides capabilities of MLP NNs, it uses Back Propagation (BP) Gradient Descent (GD) training; therefore, NNs face with not only impertinent classification accuracy but also getting stuck in local minima as well low-con...

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...

The accumulation of contaminating materials on the rotor blades of a gas turbine flowmeter is a condition of concern to the manufacturers, since it can lead to loss of calibration. Over time, a deposit of tar and heavy oil mixed with sand and dust can build up on the rotor blades, which causes the meter factor to change from its original value of calibration. A novel neural-network technique is...

We propose a reconfigurable neural network structure which has capability to process supervised or unsupervised learning algorithm computation. The proposed structure is based on modular structure which can configure artificial neural network architecture flexibly. Main processing unit of the proposed structure is designed to obtain flexibility of its internal structure by specific instructions...

In this study, the performance of two neural classifiers; namely Multi Layer Perceptron (MLP) and Radial Basis Fuction (RBF), are compared for a multivariate classification problem. MLP and RBF are two of the most widely neural network architecture in literature for classification and have successfully been employed for a variety of applications. A nonlinear scaling scheme for multivariate data...

We have investigated the use of an Artificial Neural Network (ANN) for the assessment of fall-risk (FR) in patients with different neural pathologies. The assessment integrates a clinical tool based on a wearable device (WD) with accelerometers (ACCs) and rate gyroscopes (GYROs) properly suited to identify trunk kinematic parameters that can be measured during a posturography test with differen...

In this paper a Polychronous Spiking Network was applied to financial time series prediction with the aim of exploiting the inherent temporal capabilities of the spiking neural model. The performance of this network was benchmarked against two “traditional”, rate-encoded, neural networks; a Multi-Layer Perceptron network and a Functional Link Neural Network. Three non-stationary datasets were u...