Incorporating prior knowledge into black-box classifiers is still much of an open problem. We propose a hybrid Bayesian methodology that consists in encoding prior knowledge in the form of a (Bayesian) belief network and then using this knowledge to estimate an informative prior for a black-box model (e.g. a multilayer perceptron). Two technical approaches are proposed for the transformation of...

Low Probability of Intercept (LPI) radars are developed on an advanced architecture by making use coded waveforms. Detection and classification radar waveforms important in many critical applications like electronic warfare, threat to surveillance. Precise estimation parameter the type waveform will provide information about also helps develop sophisticated intercept receiver. The present work ...

Audio content description is one of the key components to multimedia search, classification and source identification. This project examines precision of audio content description based on spectral information only on one hand, and spectral and temporal on the other. Multilayer neural network with varied parameters is used to classify musical instruments based on obtained descriptors.

An attempt has been made to evaluate the feedbacks of library users of four different libraries by using neural network based data mining techniques. This paper presents the results of a survey of users’ satisfactory level on four different libraries. The survey has been conducted among the users of four libraries of educational institutions of Kovai Medical Center Research and Educational Trus...

This paper presents DMP3 (Dynamic Multilayer Perceptron 3), a multilayer perceptron (MLP) constructive training method that constructs MLPs by incrementally adding network elements of varying complexity to the network. DMP3 differs from other MLP construction techniques in several important ways, and the motivation for these differences are given. Information gain rather than error minimization...

The purpose of this paper is to provide a quick overview of neural networks and to explain how they can be used in control systems. We introduce the multilayer perceptron neural network and describe how it can be used for function approximation. The backpropagation algorithm (including its variations) is the principal procedure for training multilayer perceptrons; it is briefly described here. ...