ABSTRACT
With the dawn of the genome era computational methods in the automatic analysis of biological data have become increasingly important. The explosion in the production rate of expression level data has highlighted the need for automated techniques that help scientists analyze, understand, and cluster (sequence) the enormous amount of data that is being produced. Example of such problems are analyzing gene expression level data produced by microarray technology on the genomic scale, sequencing genes on the genomic sc ....etc

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ABSTRACT
Location prediction serves to save capacity on the air interface of mobile radio networks. A selection of neural networks of the feed-forward and feedback type are examined to prove their suitability for this purpose. As first results preferable network structures, input vectors, learning parameters and the simulated prediction probabilities are presented. A comparison with conventional methods shows the advantages and disadvantages of the use of neural networks for motion prediction. The results show that t ....etc

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Neural Networks for Handwritten character and Digits
Abstract: This article chronicles the development of an artificial neural network designed to recognize handwritten digits. Although some theory of neural networks is given here, it would be better if you already understood some neural network concepts, like neurons, layers, weights, and back propagation. The neural network described here is not a general-purpose neural network, and it's not some kind of a neural network workbench. Rather, we will focus on one very specific neural network (a ....etc

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Neural Networks for Unicode Optical Character Recognition
Abstract: The central objective of this project is demonstrating the capabilities of Artificial Neural Network implementations in recognizing extended sets of optical language symbols. The applications of this technique range from document digitizing and preservation to handwritten text recognition in handheld devices. The classic difficulty of being able to correctly recognize even typed optical language symbols is the complex irregularity among pictorial representations of the same c ....etc

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Artificial Intelligence & Neural Networks


Presented By:
Lim Kyungeun

What is AI?
Acting humanly: The Turing Test approach
Thinking humanly: The cognitive modeling approach
Thinking rationally: The laws of thought approach
Acting rationally: The rational agent approach
The Goals of AI
Example of AI in Real World
The State of The Art

]Thinking humanly: The cognitive modeling approach
The exciting new effort to make computers think ¦ machines with minds, in the full and literal sense. ....etc

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Definition
An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, thr ....etc

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OPTICAL devices

INTRODUCTION
Explosive information demand in the internet world is creating enormous needs for capacity expansion in next generation telecommunication networks. It is expected that the data- oriented network traffic will double every year. Optical networks are widely regarded as the ultimate solution to the bandwidth needs of future communication systems. Optical fiber links deployed between nodes are capable to carry terabits of information but the electronic switching at the nodes limit th ....etc

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Abstract
Most device drivers have one ulterior motive and one target to achieve - deliver the maximum using the minimum. No matter how stable or feature rich a device driver might be, if it cannot perform in terms of high throughput and low CPU utilization, it is as good as any other run of the mill driver.The objective of this topic is to use the thinking out of the box concept and expose techniques, which go beyond just good programming principles to get that extra edge which can put your next driver into the elite group of high perform ....etc

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I need MATLAB Code for character recognition using MATLAB AND Neural networks ....etc

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Abstract:-
This report explores the application of neural networks to the problem of identifying optically scanned characters in an automated manner.
Input:- scanned images of printed text.
Classification:-Use input values to determine the classification. i.e. is the input the letter A? Data Filtering:-Smooth an input signal.
i.e. noise filtering if any.
Output:-Computer r ....etc

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