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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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ns and solve problems, breaking these thought processes down
into basic steps and designing a computer program that solves problems
using those some steps .AI thereby provides a simple , structured
approach to design complex decision making programs, human intelligence
is of complex function that scientists have only began to understand,
but enough is known for us to make certain assumptions about how we
think and apply these assumptions in designing AI problems.
SUPERFAST AUTOCONFIGURING ARTIFICIAL NEURAL NETWORK:
The reasons for adapting ANNs are as follows:
¢ Massive..................[:=> 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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e number of steps verses change in capacitance response as shown in Graph 2.Then with the help of the two graphs the third graph was plotted pressure verses number of steps of the stepper ,Which is given in Graph 3.This process was repeated for the many capacitive tactels. And the pressure calibration was completed in this way. Finally it was found that stepper motor could exert pressure 19N/M2 per step.
After the calibration of the stepper motor the sensor (elastometer) was calibrated in terms of the pressure and time response. Thus the system with stepper motor used for ..................[:=> 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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of view of a 3*3 sphere of influence C.N.N cell , this implies that even though the function has 29 parameters, its evaluation requires at most the implementation of linear combination of 10 terms .

IMPLEMENTATION OF SIMPLICAL R.T.D. C.N.N.
The first block is responsible for vertex code generation, whereas the second block is responsible for producing..................[:=> 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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stination ZIP code), Digitizing hand written spreadsheets, tax forms etc. Patterns 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. Numera..................[:=> 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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y 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 particularly suitable in many sign..................[:=> 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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ighly 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 perform this instruction is truly a robot. So, the conclusion is that to be called a robot; you really need an on-board brain and a way to program it.

Classification of ROBOTS:
Robot like devices:
Prosthe..................[:=> 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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ical advancement in the last 50 years ; 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 CN..................[:=> 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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mple, 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 feedforward network is useful for many applications, however, a number of modifications have been proposed to improve its suitability for application to process systems...................[:=> 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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cation of pattern recognition is the selection of primary variables because the lower limit for the classification error depends on the primary variables.

Draw backs of conventional methods
1. The online transient stability assessment of the electrical power systems is an extremely difficult task with the available techniques.
2. Each contingency (fault) must be treated separately.
3. Smaller time step intervals are needed to ensure numerical stability.
4. Electro motive force and mechanical power inputs are assumed constant during the transient.
5. Very elaborate off line computation..................[:=> Show Contents <=:]



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