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Application of fuzzy logic In pattern recognition


Posted by: seminar class
Created at: Thursday 12th of May 2011 01:24:23 AM
Last Edited Or Replied at :Thursday 12th of May 2011 01:24:23 AM
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sifier is given by d(x,vi)=min{d(x,vk )}
Weighted approaching degree
Define a new data sample characterized by m features as a collection of non interactive fuzzy sets B={B1,B2,B3……Bn}
Each know pattern in m dimensional space is a fuzzy class (pattern) given by Ai={Ai1,Ai2……..Aim} where i=1,2,….c describes c patterns.
Some features may be more important so we introduce normalized weighing factors wj,
The equations in approaching degree concept is modified for each of the known c patterns by
Then sample B is closest to pattern Aj when
Illustration
The last st..................[:=> Show Contents <=:]



FUZZY LOGIC FOR OPTIMIZATION OF A PROBLEM


Posted by: project report helper
Created at: Monday 04th of October 2010 03:37:18 AM
Last Edited Or Replied at :Monday 04th of October 2010 03:37:18 AM
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attachment=4947]
FUZZY LOGIC
FOR OPTIMIZATION OF A PROBLEM



By
K.Harish Babu
Roll No: 1109508
M.Tech – I Semester
Industrial Engineering
Department of Mechanical Engineering
Sri Venkateswara University College of Engineering
Tirupathi-517 502 (A.P.) INDIA


Introduction:
This is the first in a series of six articles intended to share information and experience in the realm of fuzzy logic (FL) and its application. This article will introduce FL. Through the course of this article series a simple implementation will be explained in detail. Each artic..................[:=> Show Contents <=:]



pattern recognition using neural networks


Posted by: pavithra..
Created at: Monday 19th of July 2010 08:15:41 AM
Last Edited Or Replied at :Thursday 18th of November 2010 01:44:36 AM
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rk to pattern recognition and also how to code the network for the pattern we want to recognise.
Can i expect complete information on this topic? so, please send me the file ..
Thanking u..................[:=> Show Contents <=:]



PATTERN RECOGNITION - A STATISTICAL APPROACH full report


Posted by: computer science topics
Created at: Monday 07th of June 2010 07:57:38 AM
Last Edited Or Replied at :Monday 07th of June 2010 07:57:38 AM
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he separating hyper plane is iteratively updated as a function of the distances of the misclassified patterns from the hyper plane.
3.1 Classifier Combination

There are several reasons for combining multiple classifiers to solve a given classification problem. So me of them are listed below:
1. A designer may have access to a number of different classifiers, each developed in a different context and for an entirely different representation/description of the same problem. An example is the identification of persons by their voice, face, as well as handwriting.
2. Sometimes more than..................[:=> Show Contents <=:]



PH value control using Fuzzy logic


Posted by: Gouri
Created at: Sunday 07th of February 2010 02:28:27 AM
Last Edited Or Replied at :Sunday 05th of June 2011 02:48:03 AM
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Please mail me a detailed paper which includes explaination with diagramatical support on the topic Ph value ..................[:=> Show Contents <=:]



Automatic braking system using fuzzy logic


Posted by: electronics seminars
Created at: Thursday 10th of December 2009 03:55:09 AM
Last Edited Or Replied at :Tuesday 14th of February 2012 01:44:24 AM
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etermined time from the time of detection of the relative connection..................[:=> Show Contents <=:]



NEURO FUZZY LOGIC


Posted by: seminar projects crazy
Created at: Friday 30th of January 2009 12:18:04 PM
Last Edited Or Replied at :Friday 03rd of February 2012 01:05:58 AM
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late the fuzzy if-then rules. When we cannot do this, we may need neural-network techniques to generate the rules. Here arise adaptive fuzzy systems...................[:=> Show Contents <=:]



Automated Eye-Pattern Recognition Systems


Posted by: computer science crazy
Created at: Sunday 21st of September 2008 12:53:45 PM
Last Edited Or Replied at :Thursday 17th of March 2011 11:11:48 PM
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rable human features in the face, hand, voice or finger print, the patterns in the iris do not change overtime and research show the matching accuracy of iris recognition systems is greater than that of DNA testing. Positive identifications can be made through glasses, contact lenses and most sunglasses. Automated recognition of people by the pattern of their eyes offers major advantages over conventional identification techniques. Iris recognition system also require very little co-operation from the subject, operate at a comfortable distance and are virtually impossible to deceive. Iris reco..................[:=> Show Contents <=:]



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