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## cellular neural networksPosted by: electronics seminars Created at: Monday 28th of December 2009 05:07:40 AM Last Edited Or Replied at :Monday 02nd of May 2011 03:07:21 AM | cellular neural networks ppt ,
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components input to ramp signal. In this scheme vertex codes can be read at the outputs of
comparators. PARAMETER RETRIEVAL Once a vertex vi has been identified the second step is obtained ci= f(vi) .in the circuit scheme this is accomplished by memory block. INTER POLATION Once all the vertices &their corresponding values have been obtained the final value f(u) is obtained by interpolation at the vertices . Then, F = ? Ci*Bi In the circuit this operations is executed by the output capacitor, due to the fact that the fraction of time every function value ci=f(vi) is present at th.................. [:=> Show Contents <=:] | |||

## artificial neural network seminar reportPosted by: electronics seminars Created at: Tuesday 05th of January 2010 05:09:09 AM Last Edited Or Replied at :Monday 06th of February 2012 12:22:33 AM | artificial neural networks applications,
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neural network application in processing industry. An artificial neural network as a computing
system is made up of a number of simple and highly interconnected processing elements, which
processes information by its dynamic state response to external inputs. In recent times study of ANN
models have gained rapid and increasing importance because of their potential to offer solutions to
some of the problems in the area of computer science and artificial intelligence. Instead of
performing a program of instructions sequentially, neural network models explore many competing
hypothesis simultaneou..................[:=> Show Contents <=:] | |||

## cellular neural networksPosted by: electronics seminars Created at: Monday 28th of December 2009 05:07:40 AM Last Edited Or Replied at :Monday 02nd of May 2011 03:07:21 AM | cellular neural networks ppt ,
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This mechanism can be realized using a mixed signal circuit architecture illustrated where an array of comparators compare components input to ramp signal. In this scheme vertex codes can be read at the outputs of comparators. PARAMETER RETRIEVAL Once a vertex vi has been identified the second step is obtained ci= f(vi) .in the circuit scheme this is accomplished by memory block. INTER POLATION Once all the vertices &their corresponding values have been obtained the final value f(u) is obtained by interpolation at the vertices . Then, F = ? Ci*Bi In the circuit this operatio.................. [:=> Show Contents <=:] | |||

## ARTIFICIAL NEURAL NETWORK BASED POWER SYSTEM RESTORATOINPosted by: computer science crazy Created at: Monday 28th of December 2009 01:47:21 AM Last Edited Or Replied at :Monday 06th of February 2012 12:22:47 AM | RESTORATOIN,
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tion plan provided by the proposed scheme will be composed of energizing sequences and restoration
load percentage pick up values for all islands. As the final step of the total restoration, the
closing of the tie-lines will be the responsibility of the system operator. The tie-lines should be
closed when all the islands are restored and are in steady state. RESTORATION CONSTRAINTS In order to generate a feasible restoration plan to be used as a training pattern by the IRSs, certain operational constraints must be considered. The various constraints considered are: .................. [:=> Show Contents <=:] | |||

## neural network application in power electronicsPosted by: shashimandya Created at: Wednesday 09th of December 2009 08:29:39 AM Last Edited Or Replied at :Friday 20th of January 2012 10:27:22 PM | neural network applications,
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neural netw..................[:=> Show Contents <=:] | |||

## Neural NetworksPosted by: computer science crazy Created at: Thursday 03rd of September 2009 05:56:13 AM Last Edited Or Replied at :Thursday 03rd of September 2009 05:56:13 AM | neural networks graph ,
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n on the basis of trained knowledge in the training set . This is contrary to the repetitive process
of transferring the load & estimating power loss in conventional algorithm. ANN are designed to two groups: 1) The first group is to estimate the proper load data of each zone . 2)The second is to determine the appropriate system topology from input load level . In addition, several programs with the training set builder are developed for the design the training & accuracy test of A.N.N.This paper will present the strategy of feeder reconfiguration to reduce power loss, by using A.N.................. [:=> Show Contents <=:] | |||

## Artificial Neural Networks Download Seminar ReportPosted by: Computer Science Clay Created at: Thursday 30th of July 2009 06:59:34 AM Last Edited Or Replied at :Tuesday 13th of March 2012 01:57:40 AM | artificial neural networks activation functions ,
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Structure of a Neural Network section which is followed by architecture. The most important concept
of the neural networks are its wide range of its applications, a few of which will be dealt in the
consequent sections and then its limitations. The main question of interest to us would be What will
be the future of Neural Networks, Will it survive or will it rule us?â€This section leads us to
a brief conclusion and we end the paper with the references. http://www.seminarprojects.net/downloads/?file=/computer%20science%20and%20electronics/ARTIFICIAL-NE URAL-NETWORKS.pdf&name=ARTIFICIAL-.................. [:=> Show Contents <=:] | |||

## Artificial Neural Networks Download Seminar ReportPosted by: Computer Science Clay Created at: Thursday 30th of July 2009 06:52:40 AM Last Edited Or Replied at :Monday 06th of February 2012 12:22:26 AM | artificial neural networks activation functions,
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le when asked if they think computers could ever become sentient quickly respond no and refer to the
fact that computers are unable to learn. However, Neural Networks seems to do just that. Neural Networks encompass a diverse set of computational models, which share a set of simple underlying characteristics. Inspired by the computational style of biological systems, a Neural Network can be viewed as an assembly of simple, interconnected processing units (neurons) acting in parallel, which communicate to each other using unidirectional connections. Neural networks are distinguished from .................. [:=> Show Contents <=:] |

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