The application of artificial neural network to compressor performance map prediction is investigated. Different types of artificial neural networks such as general regression neural network, rotated general regression neural network proposed by the authors, radial basis function network, and multilayer perceptron network are considered. Two different models are utilized in simulating the perfo...

This paper presents a comparative study of automatic classification of different types of heart beat arrhythmias. The heart beats are classified into normal, premature ventricular contraction, atrial premature, right bundle branch block and left bundle branch block classes. Different classifiers are used in this work, namely support vector machine, multilayer perceptron neural networks, and Tre...

In this paper we present a novel classifier which integrates a multilayer perceptron and a error-correcting decoder. There are two stages in the classifier, in the first stage, mapping feature vectors from feature space to code space is achieved by a multilayer perceptron; in the second stage, error correcting decoding is done on code space, by which the index of the noisy codeword can be obtai...

This paper describes construction of multilayer perceptron by open source neural networks simulator Neuroph and Petri net. The described multilayer perceptron solves logical function "xor "exclusive or. The aim is to explore the possibilities of description of the neural networks by Petri Nets. The selected neural network (multilayer perceptron) allows to be seen clearly the advantages and disa...

ANN finds its applications in various signal processing applications such as image recognition(image processing techniques),pattern recognition, system identification, different types of filters(FIR,IIR) and other control problems. In this paper, a multilayer perceptron with more than one hidden layers is considered and for the image processing application such as image recognition, A design of...

The estimation and forecasting of the hydrologic data carry significance for many water resources engineering problems. Establishing sediment monitoring instruments on rivers is a costly operation. The methods available in literature for sediment concentration estimation are complicated, time consuming and necessitate cumbersome parameter estimation procedures. Artificial neural networks have b...

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. ...

Finding suitable jobs for US Navy sailors periodically is an important and everchanging process. An Intelligent Distribution Agent (IDA) and particularly its constraint satisfaction module take up the challenge to automate the process. The constraint satisfaction module's main task is to provide the bulk of the decision making process in assigning sailors to new jobs in order to maximize Navy a...

A multilayer perceptron is usually considered a passive learner that only receives given training data. However, if a multilayer perceptron actively gathers training data that resolve its uncertainty about a problem being learnt, sufficiently accurate classification is attained with fewer training data. Recently, such active learning has been receiving an increasing interest. In this paper, we ...