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...

In this paper, we propose an artificial neural network (ANN) as a design technique for multilayer circular microstrip antennas based on Levenberg Marquardt training algorithm for modelling, simulation and optimization. Levenberg – Marquart (LM) algorithm has been used to train the MultiLayer Perceptron Neural Networks (MLPNNs). In the design procedure, the feed forward network is defined as a s...

nowadays, software cost estimation (sce) with machine learning techniques are more performance than other traditional techniques which were based on algorithmic techniques. in this paper, we present a new hybrid model of multi-layer perceptron (mlp) artificial neural network (ann) and ant colony optimization (aco) algorithm for high accuracy in sce called multilayer perceptron ant colony optimi...

kashan aquifer is adjacent to salt lake. because of this adjacency, the saline water of the lake has moved to the aquifer. in this study groundwater quality of the aquifer was simulated using artificial neural network (ann) model. for this purpose, the dominant ion of water was first determined by piper diagram. results showed that the sodium chloride is the dominant ion of water and so it was ...

because of high cost of drilling and analysis of samples, it needs to predict gold and silvers based on pathfinder such as as, sb, cd, pb and zn and decrease the cost and time exploration project implementation. in this paper, the model based on a multilayer perceptron artificial neural network (mlp-ann) optimized by invasive weed optimization algorithm (iwo) to predict of gold and silver in za...

This paper describes artificial neural network (ANN) based prediction of theresponse of a fiber optic sensor using evanescent field absorption (EFA). The sensingprobe of the sensor is made up a bundle of five PCS fibers to maximize the interaction ofevanescent field with the absorbing medium. Different backpropagation algorithms areused to train the multilayer perceptron ANN. The Levenberg-Marq...

This study introduces the classiication of musical instrument sounds by artiicial neural networks (ANN). The time varying spectral contents of sounds are estimated based on Short-time Fourier Transform (STFT) and are applied to ANN structures for classiication. Recognition results obtained from a multilayer perceptron (MLP), time delay neural network (TDNN) and a hybrid self organizing map radi...

The aim of this study is to classify electromyogram (EMG) signals for controlling multifunction proshetic devices. An artificial neural network (ANN) implementation was used for this purpose. Autoregressive (AR) parameters of a1, a2, a3, a4 and their signal power obtained from different arm muscle motions were applied to the input of ANN, which is a multilayer perceptron. At the output layer, f...

Artificial Neural Network is widely used to learn data from systems for different types of applications. The capability of different types of Integrated Circuit (IC) based ANN structures also depends on the hardware backbone used for their implementation. In this work, Field Programmable Gate Array (FPGA) based Multilayer Perceptron Artificial Neural Network (MLP-ANN) neuron is developed. Exper...