The motor unit action potentials (MUPs) in an electromyographic (EMG) signal provide a significant source of information for the assessment of neuromuscular disorders. Since recently there were different types of developments in computer-aided EMG equipment, different methodologies in the time domain and frequency domain has been followed for quantitative analysis of EMG signals. In this study,...

BACKGROUND Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image artif...

this research develops an allometric model for estimation of biomass based on the height and dbh of trees in the hyrcanian forests of iran. an accurate allometric model reduces the uncertainty of allometric equation in biomass estimation using radar images. in this study, 317 trees were selected randomly from the 4 different dominant tree species for the development of an allometric model cover...

Abstract In this study, modeling of discharge was performed in compound open channels with non-prismatic floodplains (CCNPF) using soft computation models including multivariate adaptive regression splines (MARS) and group method data handling (GMDH), then their results were compared the multilayer perceptron neural networks (MLPNN). addition to total discharge, separation between floodplain ma...

This paper describes the implementation of a Multilayer Perceptron Neural Network for handwritten digit recognition. The paper provides the knowledge about previously implemented techniques for same application and also provides their merits and demerits. In this paper Optimal Multilayer Perceptron.Neural network has been designed to reduce complexity of the circuit. Results are also stated to ...

The crude oil prices as well as the effective exchange rate of the dollar are both time series and non -stationary as well. In this paper, we investigate the relationship between real effective exchange rate and crude oil prices by hybrid wavelet network. We use a simple Multi-layer Perceptron Neural Network (MLPNN) based wavelet decomposition to analyse the relatio nship between real effective...

The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data th...

The analysis of pathological voice is a challenging and an important area of research in speech processing. Acoustic voice analysis can be used to characterize the pathological voices with the aid of the speech signals recorded from the patients. This paper presents a method for the identification and classification of pathological voice using Artificial Neural Network. Multilayer Perceptron Ne...

In this study, prediction of the future land use cover (LULC) changes over Mumbai and its surrounding region, India, was conducted to have reference information in urban development. To obtain historical dynamics LULC, a supervised classification algorithm applied Landsat images 1992, 2002, 2011. Based on spatial drivers LULC 1992 multiple perceptron neural network (MLPNN)-based Markov chain mo...