A neural net program for pattern classification is presented, which includes: i) an improved version of Kohonen's Learning Vector Quantization (LVQ with Training Count); ii) Feed-Forward Neural Networks with Back-Propagation training; iii) Gaussian (or Mahalanobis distance) classification; iv) Fisher linear discrimination. Back-Prop trainings with emulations of Intel's ETANN and Siemens' MA16 n...

Artificial Neural Network (ANNs) techniques are recently indicating a lot of promises in the application of various micro-engineering fields. Such a use of ANNs for estimating the patch dimensions of a microstrip line feed rectangular microstrip patch antennas has been presented in this paper. An ANN model has been developed and tested for rectangular patch antenna design. The performance of th...

In some practical applications Neural Network (NN), a fast response to external events within extremely short period is required. However, using back propagation (BP) based on gradient descent optimization method obviously not satisfy many applications because of serious problems with BP are slow convergence speed of learning and containment low minima. Over the years, many improvements and mod...

Optical character recognition refers to the process of translating segmented hand-written images or typewritten images into machine editable text. In this study, we propose a Tamil palm leaf manuscripts character recognition system using FFBNN technology. First the palm leaf manuscripts characters are segmented by exploiting the sliding window and adaptive histogram calculation. Afterwards, the...

This paper presents review of application of artificial neural networks in weather classification and prediction; some existing weather forecasting models have limitations and also benefits of neural network are discussed in this paper. Accurate weather prediction is important in today’s world as agricultural sector is widely dependent on it. Since there is non-linearity in weather data therefo...

Digital Images are contaminated by noise during acquisition and/or transmission over communication channel. Eliminating impulse noise and uniform noise from the images without damaging their boundaries and fine details is an important and a challenging task in the image processing applications. A nonlinear technique based on decision mechanism for suppressing impulse noise and uniform noise fro...

Feed-Forward (FF-) and Feed-Back (FB-) structures have been proposed for Blind Source Separation (BSS). The FF-BSS systems have some degrees of freedom in the solution space, and signal distortion is likely to occur in convolutive mixtures. On the other hand, the FBBSS structure does not cause signal distortion. However, it requires a condition on the propagation delays in the mixing process. I...

Moving vehicle location prediction method mainly based on their spatial and temporal data . The moving objects has been developed as a specific research area of Geographic Information Systems (GIS). Most of the techniques have been used for performing the vehicle movement detection and prediction process. This type of work is a lack of analysis in predicting the moving vehicles location in curr...

Cancer is the most important cause of death for both men and women. The early detection of cancer can be helpful in curing the disease completely. So the requirement of techniques to detect the occurrence of cancer nodule in early stage is increasing. A disease that is commonly misdiagnosed is lung cancer. Artificial Neural Networks (ANNs) play a vital role in the medical field in solving vario...

In this paper, a variant of Backpropagation algorithm is proposed for feed-forward neural networks learning. The proposed algorithm improve the backpropagation training in terms of quick convergence of the solution depending on the slope of the error graph and increase the speed of convergence of the system. Simulations are conducted to compare and evaluate the convergence behavior and the spee...