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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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of cells c(i,j) with Cartesian co-ordinates. Considering inputs and outputs of
a cell as binary arguments. It can realize Boolean functions. using this technology,
analog computers mimic anatomy & physiology of many sensory& processing organs with
stored programmability. this has been called sensor revolution with cheap sensors &mems
arrays in desired forms of artificial eyes, ears, nose etc. Such a computer is
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## 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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is trained on line. And the weights of connections are updated during each sampling interval. In
this caseâ„¢ the cost function is the plant output error rather than the networks output error.
The configuration of DAC is shown in figure. The limitation of using this configuration is that one must have the some knowledge about the plant dynamics i.e. Jacobin matrix of the plant. To solve the problems; initially, Psaltis D.et al proposed a technique for determining the partial derivatives of the plant at its operating point Xianzhang et al and Yao Zhang et al presented a simple approach.................. [:=> 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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f fading memory. the CNN UM is a common computational paradigm for as diverse fields of
spatio-temporal computing as for example, retinal model, reaction diffusion equations, mathematical
morphology, etc. The stored program ,as a sequence of templates is considered as a genetic code
of CNN UM. The elementary genes are the templates. .................. [:=> 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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ally changing its weight connections. Supervised learning algorithms are commonly used in
engineering processes because they can guarantee the output. In this power system restoration scheme, a multilayered perceptron(MLP) was used and trained with a supervised learning algorithm called back-propagation. A MLP consists of several layers of processing units that compute a nonlinear function of the internal product of the weighted input patterns. These types of network can deal with nonlinear relations between the variables; however, the existence of more than one layer makes the weight adj.................. [:=> 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 network application in power elec..................[:=> 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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patterns which minimizes the loss under given conditions..................[:=> 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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works 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 in the comparison between brain and neural networks as well as neurons
and perceptrons are made with the help of figures. The most basic component of a neural network is
the perceptron, which is called the artificial neuron, is studied and depicted in the Structure of
a Neural Net..................[:=> 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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after the functioning of human brain. Most Neural Networks have some sort of training rule whereby
the weights of connections are adjusted on the basis of presented patterns. In other words, Neural
Networks learn from examples, just like children learn to recognize dogs from examples of dogs and
exhibit some structural capability for generalization. The most significant aspects of Neural Networks are that they allow the computer to learn and they have the potential for parallelism. This means that they allow the computer to solve multiple problems at a time. Neural Networks can perform .................. [:=> Show Contents <=:] |

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