In this paper we present a neural network based spectrum classifier (NSC) and its application to ultrasonic resonance spectroscopy. The use of an Artificial Neural Network (ANN) is proposed to meet the requirements of high sensitivity for small but relevant changes in the spectra, and simultaneous robustness against measurement noise. Provided with enough training examples, the ANNs are known t...

ML and DL algorithms are becoming more popular to predict household food security status, which can be used by the governments policymakers of country provide a supply for needy in case emergency. models, namely: k-Nearest Neighbor (kNN), Logistic Regression (LR), Support Vector Machine (SVM), Naive Bayes (NB), Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN) Convolutional network (...

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 arti...

abstract evapotranspiration as one of the important elements in agriculture has a considerable role in water resource management. therefore, using a more exact estimation method is an essential step of agricultural development, especially in arid semi-arid area. in this research, in order to exact estimate of garlic evapotranspiration using lysimeteric data, an artificial neural network (ann) m...

A multilayer perceptron is a feed forward artificial neural network model that maps sets of input data onto a set of appropriate output. It is a modification of the standard linear perceptron in that it uses three or more layers of neurons (nodes) with nonlinear activation functions and is more powerful than the perceptron in that it can distinguish data that is not linearly separable, or separ...

This paper presents an application of Artificial Neural Networks (ANNs) to predict daily solar radiation. We look at the Multi-Layer Perceptron (MLP) network which is the most used of ANNs architectures. In previous studies, we have developed an ad-hoc time series preprocessing and optimized a MLP with endogenous inputs in order to forecast the solar radiation on a horizontal surface. We propos...

Artificial neural network based equalizers can be used for equalization in coherent optical OFDM systems. The artificial neural network based multilayer layer perceptron is a feed-forward network consists of one hidden layer with one or more hidden nodes between its input and output layers and can be trained by using back propagation algorithm. However, this algorithm suffers from slow converge...

An artificial neural network (ANN) provides a mathematically flexible structure to identify complex nonlinear relationship between inputs and outputs. A multilayer perceptron ANN technique with an error back propagation algorithm was applied to a multitime-scale prediction of the stage of a hydrologically closed lake, Devils Lake (DL), and discharge of the Red River of the North at Grand Forks ...

In this paper, a new method of bandwidth estimation using variation of slot length on interdigital band pass filter has been presented using artificial neural networks for desired frequency range between 1.7—2.5 GHz. Interdigital filter is multifinger periodic structure which offers compact filter design space. An ANN model has been developed and tested for estimating the cut off frequency of b...

A functional relationship between two variables, applied mass to a weighing platform and estimated mass using Multi-Layer Perceptron Artificial Neural Networks is approximated by a linear function. Linear relationships and correlation rates are obtained which quantitatively verify that the Artificial Neural Network model is functioning satisfactorily. Estimated mass is achieved through recallin...