Applications of neural network

    • [DOC File]An Application Example of Neural Network based ...

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      A Self Learning Neural Network was designed with the scope of denoising and detecting the anomalies (i.e., spikes) on the signals obtained by a simulation of a system gear. In order to check the ability of the network to detect and to put in evidence the anomalies, random white noise was …

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    • Neural Networks Models for visual lipreading System

      5.0 Network Selection. Because all artificial neural networks are based on the concept of neurons, connections and transfer functions, there is a similarity between …

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    • [DOC File]Artificial Neural Networks Technology

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      Artificial neural networks, analysis, sensitivity, graph theory. 1 Introduction. Neural Networks have been used as an effective method for solving engineering problems in a wide range of application areas. In most of the applications it is essential to be able to ensure that the …

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    • Neural Network Definition

      Neural Network-based Classification and Experimental Results. In this study, to simplify the computation complexity, we chose a three-layer neural architecture as the basic architecture. To perform a neural network-based classification, the first task is to determine the number of input bands and the number of the classes to be derived from the ...

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    • [DOC File]Neural Network Applications Development

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      At the topmost layer of applications, neural network techniques are employed in speech processing [29-32], smoothing of video delay variations [33], data mining [34-35], image coding [36-38], clone detection [39-40], growth prediction [41], and marketing support [42-43].

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    • [DOC File]Neural Networks:

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      A survey of the applications of neural network models for Visual lip-reading. B Sujatha † and T Santhanam †† , sujatha_basdas@yahoo.co.in santhanam_dgvc@yahoo.com

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    • [DOC File]An application of a self learning neural network for ...

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      Neural Network Development Methodology. Aims to add structure and organisation to neural network applications development to reduce cost, increase accuracy, consistency, user confidence and friendliness. The Concept Phase. Involves. 1. validating proposed application, and. 2. …

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