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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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f the form ( +1,-1,+1,-1) it was proven that the set of all PWL function f is a linear
vector space. Every PWL function can be expressed as a linear combination F= â€šÂ¬ CiAi (u) Ai(v-j)=1, if i=j VERTEX - CODE GENERATION The first step is to identify the simplex that contains the given input vector u.Notice here that there are n! different simplices in (3), and every simplex is identified by the coordinates of its n+ 1 vertex. This mechanism is based on the result, U= ? B Vij This mechanism can be realized using a mi.................. [:=> 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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resented a simple approach, in which by using the sign of the plant Jacobin. The modifications of
the weights are carried out. 4.3 INDIRECT ADAPTIVE CONTROL Narendra K S et al. Presented an indirect adaptive control strategy. In this approach, two neutral networks for controller purpose and another for plant modeling and is called plant emulator decides the performance of the controller. The configuration of indirect adaptive control scheme becomes as shown FIG.3. In direct learning the neutral controller, it is well known that the partial derivatives of the controlled plant out.................. [:=> 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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y assume and take for ranted that, for any sequence of instructions: (a) All the transients decay with in a specified clock cycle,& (b) All the signals remain with in a prescribed range of dynamics (including dissipation, slope, etc.). A unique feature of the CNN dynamics & the CNN-UM architecture is that we can assure conditions (a) & (b) as well. It is much less trivial here than in the digital case .Our main elementary instructions are the CNN templates & the local logic operations. But the CNN templates may induce the most exotic dynamics . the global clock( .................. [:=> 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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gh non-linearity can be more accurate than other methods. These non-linear computational elements
will be working in unison to solve specific problems. ANN is configured for specific applications
such as data classification or pattern recognition through a learning process. Learning involves
adjustment of synaptic connections that exist between neurons. ANN can be simulated within
specialized hardware or sophisticated software. ANNs are implemented as software packages in
computer or being used to incorporate Artificial Intelligence in control systems. BIOLOGICAL NEURON The m.................. [:=> 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 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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systems. This study is intended to purpose the strategies to reconfigure the feeders by using artificial neural n/w s with the mapping ability. Artificial neural n/w's determine the appropriate system topology that reduces the power loss according to the variation of load pattern. The control strategy can be easily obtained on the basis of system topology which is provided by artificial neural networks. Artificial neural networks determine the most appropriate system topology according to the load pattern on the basis of trained knowledge in the training set . This is contrary to the repe.................. [:=> 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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e process create something new, so Neural computing is an attempt at modeling the workings of a
brain and this presentation is an attempt to understand the basic concept of artificial neural
networks. In this paper, a small but effective overall content of artificial neural networks is presented . .First,the history of Neural Networks which deals with the comparative study of how vast the Neural Networks have developed over the years is presented. Next, having known what exactly is a neural network with the help of a MLP model, we proceed to next session: resemblance with brain where.................. [:=> 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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ty of tasks just as any regular computer. They are of greatest use in computing problems where the
input does not follow clean strict rules but instead has an overall pattern. Neural Networks have
applications in diverse areas like interpretation, prediction, diagnosis, planning, monitoring,
debugging, repair, instruction, control, categorization and pattern recognition. Thus Neural
Networks is an exponentially growing area of real- time applications of the new era. http://www.seminarprojects.net/downloads/?file=/computer%20science%20and%20electronics/ARTIFICIAL-NE URAL-NETWORKS.pdf&name=AR.................. [:=> Show Contents <=:] |

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