[PDF] Top 20 Threshold Prediction of a Cyclostationary Feature Detection Process using an Artificial Neural Network

Threshold Prediction of a Cyclostationary Feature Detection Process using an Artificial Neural Network

... as an intelligent way of utilizing the spectrum efficiently depending on the ...forms of distortion and disturbances depending on the factors like distance, transmission medium and so ...types ... See full document

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A RECURRENT ELMAN NEURAL NETWORK - BASED APPROACH TO DETECT THE PRESENCE OF EPILEPTIC ATTACK IN ELECTROENCEPHALOGRAM (EEG) SIGNALS

... By using Elman Neural Network and Approximate Entropy(ApEn) as an input feature for implementation of detection of ...is using a single input feature ... See full document

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AN ANN APPROACH FOR NETWORK INTRUSION DETECTION USING ENTROPY BASED FEATURE SELECTION

... build an efficient intrusion detection system which can exhibit low false alarm rate and high detection ...consists of two major layers as depicted in ...removed using three entropy ... See full document

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Hybrid Intelligent Approach for Predicting Product Compositions of a Distillation Column

... control of distillation process. The product compositions of distillation columns are traditionally measured using indirect techniques via inferring tray compositions from its temperature or ... See full document

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HYBRIDIZATION OF ARTIFICIAL NEURAL NETWORK USING DESIRABILITY FUNCTIONS FOR PROCESS OPTIMIZATION

... response of a neuron. The sum of the weighted input signal (net input) is applied with an activation to obtain the ...are of great interest in all neural network ...justifies ... See full document

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Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks

... applicability of ANN in different nontraditional machining processes such as, Kuo Tsai et ...ability of different neural networks models to predict the surface finish based on the effect of ... See full document

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Prediction of Operating Characteristics of Electrotechnical Devices using Artificial Neural Networks

... finding an appropriate neural network, able to simulate the behavior of proximity sensor at different functioning conditions, we choose a high degree of parameterization for the ... See full document

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Early Detection of Lung Cancer Using Neural Network Techniques

... sets. An efficient lung nodule detection scheme with accuracy of ...combination of image processing and data mining ...done using Genetic Algorithm (GA) [28] and morphological image ... See full document

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Prediction of ferric iron precipitation in bioleaching process using partial least squares and artificial neural network

... properties of such a network is reliant on the computational elements, especially the weights and the transfer function, in addition to the net topo- ...the network topology and the transfer function ... See full document

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Prediction of Skin Penetration using Artificial Neural Network

... was an empirical variable and did not give the actual structural features of the chemical compounds that influence skin ...features of molecules and improve the precision of the model 15, 16 ... See full document

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Automatic detection of thermal damage in grinding process by artificial neural network

... develop an intelligent system for detecting the workpiece burn in the surface grinding process by utilizing a multi-perceptron neural network trained to generalize the process and, in ... See full document

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URBAN GROWTH MODELING USING AN ARTIFICIAL NEURAL NETWORK A CASE STUDY OF SANANDAJ CITY, IRAN

... possibility of learning, is an appropriate tool for environmental ...composed of input layer, intermediate layers and an output ...type of networks is used to identify non- linear ... See full document

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Artificial neural network for prediction of the area under the disease progress curve

... ABSTRACT: Artificial neural networks (ANN) are computational models inspired by the neural systems of living beings capable of learning from examples and using them to solve ... See full document

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Nodules Segmentation in Breast Ultrasound using the Artificial Neural Network Self-Organizing Map

... technique using an artificial neural network type self-organizing, in order to locate and delimit the lesion contour as accurately as ...object of interest and junction of ... See full document

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Arq. NeuroPsiquiatr. vol.66 número2A

... duration of crises (13) after critical events, including mental confusion, sleepiness, paralyses, vomiting and body ache; (14) generalized tonic, clonic, tonic-clonic, absence seizure (petit mal), atonic signs and ... See full document

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Short-Term Load Forecasting Using Artificial Neural Network

... Abstract--Artificial neural network (ANN) has been used for many years in sectors and disciplines like medical science, defence industry, robotics, electronics, economy, forecasts, ...property ... See full document

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Application of Artificial Neural Network For Path Loss Prediction In Urban Macrocellular Environment

... performance of ANN model, therefore the choice of inputs to be used become ...height of base station antenna (h BS ), height of building (h b ), separation distance between buildings (∆h e ), ... See full document

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Artificial Neural Network for Precipitation and Water Level Predictions of Bedup River

... part of Sadong Basin and is situated approximately 80 km away from ...area of the catchment is 48 km 2 ...mainly of shrubs, low plant and ...type of channel ...point of the stream to ... See full document

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Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

... nance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the ...curate prediction of the incipient fault in transformer oil because each method is ... See full document

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Artificial Neural Network : A Brief Overview

... for an intelligence robot to perceive its ...number of modular neural networks to recognize multiple classes of objects for a robotic ...population of the modular neural networks ... See full document

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