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AUTOCONFIGURING ARTIFICIAL NEURAL NETWORK APPLIED TO FAULT DIAGNOSIS IN POWER SYSTEMS


Posted by: computer science technology
Created at: Sunday 24th of January 2010 06:39:12 AM
Last Edited Or Replied at :Monday 06th of February 2012 12:24:21 AM
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ade by taking a sample models of power systems. The
all possible faults of the system were diagnosed and predicted with the
help of Auto-Configuring Artificial Neural Network namely Radial
Basis Function Network and the comprehensive study reveals that the
proposed method is more efficient, faster and reliable than any other
method used for fault diagnosis of power systems.
DEFINITION:
Artificial intelligence (AI) is simply the way of making the computer
think intelligently. It there by provides a simple, structured approach
to designing complex decision-making programs...................[:=> Show Contents <=:]



TACTILE SENSING SYSTEM USING ARTIFICIAL NEURAL NETWORKS full report


Posted by: computer science technology
Created at: Sunday 24th of January 2010 04:06:02 AM
Last Edited Or Replied at :Sunday 24th of January 2010 04:06:02 AM
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the pressure. Fig 1 shows the configuration of the system. The conductive elastomer is mounted on 8*8 force sensing sites for the measurement of pressure distribution on the object. These force sensing sites are connected through the PC add-on data acquisition card. Stepper motor is used to apply specific amount of pressure for proper identification of the objects. Hardware for scanning the matrix and related signal conditioning is designed along with the stepper motor interface circuitry. Once the image of the object is acquired through the tactile sensing system then it is ..................[:=> Show Contents <=:]



cellular neural networks


Posted 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
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corresponding r.t.d.


C.N.N. UNIVERSAL MACHINE

The first spatio temporalanalogic array computer is CNN universal machine. The two different operations are continous-time, continues valued spatio-temporal nonlinear array dynamics (2-d$3-darrays) local & global logic hence analog &logic operations are mixed and embedded in array computer. Therefore we call this type of computing: analogic.
The CNN-UM architecture
(1) It has a minimum number of component types
(2) Provides stored programmability spatio temporal array computing
(3) Is ..................[:=> Show Contents <=:]



Digit Recognition using Neural Network


Posted by: Electrical Fan
Created at: Saturday 14th of November 2009 05:33:37 AM
Last Edited Or Replied at :Thursday 19th of January 2012 10:33:35 PM
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slightly shifted, distorted and even overwritten can be correctly recognized. Neural network aids in efficient recognition. A Multilayer Neural network trained with Backpropagation algorithm is used. Kirsch masks are adopted for extracting feature vectors and a multy layer clustered neural network is used for classifying numerals efficiently. The neural network will be trained with a database consisting of handwritten digits provided by writers of various ages with many different sizes and writing styles. Numerals poorly drawn or cannot be classified are rejected. A very high recognition rate,..................[:=> Show Contents <=:]



Face Recognition Using Artificial Neural Networks


Posted by: nit_cal
Created at: Saturday 31st of October 2009 04:58:30 AM
Last Edited Or Replied at :Saturday 20th of April 2013 12:55:41 AM
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sily recognizable objects. The concepts of Neural Networks have been motivated right from its inception, by the recognition that the human brain computes in an entirely different way from the conventional digital computers. The brain modeling techniques opens a new era of Computer System that learns, from experience and uses its experiential knowledge next time. This biologically inspired method is being touted as the wave of the future in computing, relieving the programmer from the cubicle of traditional algorithmic problem solving. Inherent non-linearity property of Neural Networks makes it..................[:=> Show Contents <=:]



Emerging Trends In Robotics Downlaod Seminar Report


Posted by: Computer Science Clay
Created at: Thursday 30th of July 2009 06:46:58 AM
Last Edited Or Replied at :Thursday 30th of July 2009 06:46:58 AM
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ol systems used to stabilize the position, motion, and other forces of the robot, but also to allow robots to effectively work via sensors and actuators in dynamic environments.

The field of robotics has its origin in science fiction, the term ROBOT was derived from the English translation of a fantasy play written in Czecholosolvakia around 1920. It took another 40 years before the modern technology of industrial ROBOTS began. Today robots are highly automated mechanical manipulators controlled by computers.

First, letâ„¢s decide what a Ëœrobotâ„¢ is. To be a robot, it should ..................[:=> Show Contents <=:]



Cellular Neural Network


Posted by: Computer Science Clay
Created at: Tuesday 24th of February 2009 12:56:26 PM
Last Edited Or Replied at :Sunday 21st of November 2010 10:46:10 PM
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ears ; we see the first revolution which led to pc industry in 1980's, second revolution led to internet industry in 1990's cheap sensors & mems arrays in desired forms of artificial eyes, nose, ears etc. this third revolution owes due to C.N.N.This technology is implemented using CNN-UM and is also used in imageprocessing.It can also implement any Boolean functions.

ARCHITECTURE OF CNN

A standard CNN architecture consists of an m*n rectangular array of cells c(i,j) with Cartesian coordinates (i,j) i=1,2¦..M, j=12¦...N.

A class -1 m*n standard CNN is defined by a m*n rectangular..................[:=> Show Contents <=:]



Industrial Applications using Neural Networks


Posted by: computer science crazy
Created at: Monday 22nd of September 2008 12:08:04 AM
Last Edited Or Replied at :Thursday 05th of August 2010 12:43:13 PM
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orward network. This type of network comprises an input layer where input information is presented to the network, one or more hidden layers where neuron processing takes place and an output layer from which the network outputs are obtained. It is termed a feed forward network because the outputs from one layer are fed forward as inputs to the subsequent layer. The topology of such layered networks is usually described according to the number of nodes in each layer. For example, a network with 2 inputs, 1 hidden layer with 4 nodes and 1 output is referred to as a 2-4-1 network. This basic feed..................[:=> Show Contents <=:]



Transient Stability Assessment using Neural Networks


Posted by: computer science crazy
Created at: Monday 22nd of September 2008 12:07:56 AM
Last Edited Or Replied at :Tuesday 19th of October 2010 05:02:49 AM
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erators from the rest of the system indicating loss of synchronism is detected. Even for small power network and simple mathematical model possible this method is slow and cumbersome.

The second method of Lyapunov:
In this method, the integration off post fall system equation is replaced by stability criterion. The value of a suitably designed lyapunov function v is calculated at the instant of last switching in the system and compared with the previously determined critical value Vcr of this function if V is smaller than Vcr the system will reach a stable equilibrium point.

Pattern r..................[:=> Show Contents <=:]



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