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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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fast due to the hybrid two stage training
scheme employed.
b) They have only a single hidden layer with growing number of
neurons during learning to achieve an optimal configuration.
c) Only a single network parameter called spread factor (SF) is
varied.
LIMITATIONS:
¢ Requires more training data for more accurate results.
¢ Unworthiness to detect multiple faults due to more piece of
equipment malfunctioning.
REFRENCES:
1) Sharestani.S.A, Silartis.J.Y.P Application of pattern recognition
to identification of power faults, electric power system research.
2) Fause..................[:=> 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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0.5 for correct class.

For this experiment the position of the object is varied over the array of the sensor. And the moments were calculated for the same object. Then the network was trained with the help of three sets of data by varying its position. Then was observed that network was successful to identify the object which was not included in the training set of the object.

Size of square was varied as 2X2,4X4 ,6X6.Invariant moments calculated from these objects and network was trained then network was given set of the data which was not included in the training and i..................[:=> 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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th cheap pc. Actually the DSP is a reduced instruction set (RISC). Processor used for calculating CNN dynamics
New dsp packages host 4-8 dsp processors in a chip .hence the process numbers are 4-8 times higher .since for the calculation of CNN dynamics ,a major part of dsp is not used , a special purpose chip (castle) have been developed

SIMPLICAL CNN
Recently a novel structure has been introduced to implement any Boolean / gray level function of any number of variables .The output is no longer restricted to be binary so that CNNs with gray scale outputs are obtained. Simplical CNNs a..................[:=> 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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rly drawn or cannot be classified are rejected. A very high recognition rate, even above 90% could be obtained while using neural network..................[:=> 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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different way from the conventional digita..................[:=> 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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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, let™s decide what a ˜robot™ is. To be a robot, it should have the ability to think “ make decisions. This may sound hard

IF FRONT LEFT WHISKER SENSOR IS ON THEN

STOP, GO BACKWARDS 2 FEET, TURN RIGHT, CONTINUE.

This is a very common ËœIF-THENâ„¢ statement.

A machine that can perf..................[:=> 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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cture 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 array of cells cij located at site (i,j) i= 1,2 ¦¦.m ,j=1,2,¦.n is def..................[:=> 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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d control algorithms. In process control, for example, the model can be incorporated within a model based predictive control (MBPC) algorithm, such as Generalised Predictive Control.

Alternatively, for process monitoring, the residuals (prediction errors) from such models can be analyzed to detect abnormal operation. Such monitoring and control schemes have found widespread application in industry and have led to significant improvements in process operations. Unfortunately, the models employed within the schemes tend to be linear in form. Although linear models can provide acceptable perfo..................[:=> 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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the requirements of reliable service in electrical power system is to maintain the synchronous machines running in parallel with adequate capacity to meat the low demand with the growing stress on present days power systems, the potential impact of faults and other disturbances on their security is increasing. Protective relays in the power system detect faults and trigger the opening of circuit to isolate the fault. The power system can be considered to go through changes in configuration in three stages, from a prefault, faulted to a post faults system. The analysis required knowing whether ..................[:=> Show Contents <=:]



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