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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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f triangle, we get
µI (85,50,45)= 1-5/60 =0.916
µR (85,50,45)= 1-5/90 =0.94
µIR (85,50,45)= 1-max(5/60,5/90) =0.916
µE (85,50,45)= 1-40/180 =0.78
µT (85,50,45)= 1/180min(3.35,3(5),2/5,40) = 0.05
Thus x0 most closely resembles the right triangle pattern
Let us take the case when the new data sample is a fuzzy set itself and for this we need the notion of fuzzy vectors
Formally a vector a =(a1,a2…….an) is called a fuzzy vector if for ..................[:=> 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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t 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 article will include additional outside resource reference for interested readers.

Fuzzy logic is a problem solving control methodology that lends itself to implementation in system ranging from simple, small, embedded microcontollers to large, networked, multi channel computers or work station based data acquisition and control sys..................[:=> 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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pavithra studying M.Tech production engineering. I wanna do a seminars on PATTERN RECOGNITION USING NEURAL NETWORKS.. I dont know how to relate neural network to pattern recognition and also how to code the network for the pattern ..................[:=> 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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h different types of misclassifications. For known class conditional densities, the Bayes decision rule gives the optimum classifier, in the sense that, for given prior probabilities, loss function and class -conditional densities, no other decision rule will have a lower risk (i.e., expected value of the loss function, for example, probability of error). If the prior class probabilities are equal and a 0/1 loss function is adopted, the Bayes decis ion rule and the maximum likelihood decision rule exactly coincide.
The third category of classifiers is to construct decision boundaries directly..................[:=> 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 control sing FUZZY L..................[:=> 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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er to accelerate the vehicle and maintain a fixed separation distance and drive behind the object in a tracking mode
A collision avoidance judging section is provided which, based on a relative connection between own vehicle and preceding vehicle, carries out a judgment as to whether or not a possible collision is avoidable by operating at least one of a steering wheel and a brake pedal, and a collision avoidance estimating section is provided which, based on the relative connection, carries out an estimation as to whether or not, after expiration of a predetermined time from the time of d..................[:=> 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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ally, fuzzy systems work well when we can use experience or introspection to articulate 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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¢s complex society. With only passwords, or Social Security Numbers as identity or security measures every one is vulnerable to invasion of privacy or break of security. Traditional means of identification are easily compromise and enyone can use this information to assume anotherâ„¢s identity. Sensitive personal and corporate information can be assessed and even criminal activities can be performed using another name. Eye pattern recognition system provides a barrier to and virtually eliminates fraudulent authentication and identity privacy and safety controls privileged access or auth..................[:=> Show Contents <=:]



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