This paper covers the problem of Collision Free Path Planning for an autonomous robot and proposes a solution to it through the Back Propagation Neural Network. The solution is transformed into a composition of matrix-multiplication operations, which is a classic example of problems that can be efficiently parallelized. This paper finally proposes a parallel implementation of this matrix-multip...

Multilayered feed-forward neural networks trained with back-propagation algorithm are one of the most popular “online” artificial neural networks. These networks are showing strong inherit parallelism because of the influence of high number of simple computational elements. So it is natural to try to implement this kind of parallelism on parallel computer architecture. The Parallel Hybrid Ring ...

Cell assembly is one of explanations of information processing in the brain, in which an information is represented by a firing space pattern of a group of plural neurons. On the other hand, effectiveness of neural network has been confirmed in pattern recognition, system control, signal processing, and so on, since the back propagation learning was proposed. In this study, we propose a new net...

ABSTRACT Introduction High-intensity rehabilitation training will produce exercise fatigue. Objective A backpropagation (BP) network neural algorithm is proposed to predict sports fatigue based on electromyography (EMG) signal images. Methods The principal component analysis used reduce the dimension of EMG features. knee joint angle estimated by regularized over-limit learning machine and BP a...

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...

Recently, artificial neural networks have been successfully applied to various hydrologic problems. This paper proposed flood water level modeling using the Hybrid of Back Propagation Neural Network with Extended Kalman Filter and the Hybrid of Elman Neural Network with Extended Kalman Filter that using the water level data from Sungai Kelang which is located at Jambatan Petaling, Kuala Lumpur....

yarn tenacity is one of the most important properties in yarn production. this paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. the artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 ne. as the first step for modeling, the empirical data is col...