<span lang="EN-US">Recently, navigation in an unknown environment without hitting obstacles was considered a big challenge faced by researchers. The difficulty finding good mathematical model for the different systems is deciding to use artificial intelligent controllers control mobile robot movement. In this paper, designing two multi-layer-perceptron neural networks (MLP-NN) done moveme...

In today’s world, gigantic amount of data is available in science, industry, business and many other areas. This data can provide valuable information which can be used by management for making important decisions. But problem is that how can find valuable information. The answer is data mining. Data Mining is popular topic among researchers. There is lot of work that cannot be explored till no...

This letter proposes a new type of neurons called multithreshold quadratic sigmoidal neurons to improve the classification capability of multilayer neural networks. In cooperation with single-threshold quadratic sigmoidal neurons, the multithreshold quadratic sigmoidal neurons can be used to improve the classification capability of multilayer neural networks by a factor of four compared to comm...

In this paper, work has been performed to recognize Handwritten English Character using a multilayer perceptron with one hidden layer. The feature extracted from the handwritten character is Boundary tracing along with Fourier Descriptor. Character is identified by analyzing its shape and comparing its features that distinguishes each character. Also an analysis was carried out to determine the...

Absrracf In this paper, the KIII dynamic neural network i s introduced and it is applied to the prediction of complex temporal sequences. I n our approach, Klll gives a step-by-step prediction of the direction of the currency exchange rate change. Previously, various multiplayer perceptron (MLP) networks and recurrent neural networks have been successfully implemented for this application. Resu...

Multilayer perceptrons with hard-limiting (signum) activation functions can form complex decision regions. It is well known that a three-layer perceptron (two hidden layers) can form arbitrary disjoint decision regions and a two-layer perceptron (one hidden layer) can form single convex decision regions. This paper further proves that single hidden layer feedforward neural networks (SLFN's) wit...

The model of the hybrid neural network is considered. This model consists of model ART-2 for clustering and perceptron for preprocessing of images. The perceptron provides invariant recognition of objects. This model can be used in mobile robots for recognition of new objects or scenes in sight the robot during his movement.

This work aims at classifying the body sways based on principal components of elliptical sway area (EA) and mean velocity (MV) of center of pressure by perceptron neural network. A sample of 27 young, healthy male adults was monitored during a stabilometric test, standing on a force platform during 3 min, with eyes closed, and feet in a closed position. The data were stored in a matrix, where r...