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## Application of fuzzy logic In pattern recognitionPosted 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 | application of fuzzy logic in pattern recognition ,
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ter classifier 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 IllustrationThe.................. [:=> Show Contents <=:] | |||

## FUZZY LOGIC FOR OPTIMIZATION OF A PROBLEMPosted 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 | constraint optimization problem example ,
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red significant error and significant rate of change of error, but exact values of these numbers are
usually unless very responsive performance is required in which case empirical tuning would
determine them .................. [:=> Show Contents <=:] | |||

## pattern recognition using neural networksPosted 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 | networks,
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agud evng sir/msdam. Iam pavithra studying M.Tech production engineering. I wanna do a seminars on
PATTERN RECOGNITION USING NEURAL NETWORKS.. I dont know how to relate neura..................[:=> Show Contents <=:] | |||

## PATTERN RECOGNITION - A STATISTICAL APPROACH full reportPosted 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 | pattern recognition algorithms ,
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unction, the Bayes decision rule can be simplified as follows (also called the maximum a posteriori
(MAP) rule): Assign input pattern x to class wi if P( wi I x) > P (wj I x) for all j ? i (3) Various strategies are utilized to design a classifier in statistical pattern recognition, depending on the kind of information available about the class-conditional densities. 2.1 Dimensionality Reduction There are two main reasons to keep the dimensionality of the pattern representation (i.e., the number of features) as small as possible: measurement cost and classification accuracy. A li.................. [:=> Show Contents <=:] | |||

## PH value control using Fuzzy logicPosted 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 | PH value control using Fuzzy logic,
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Please mail me a detailed paper which includes explaination with diagramatical support on the topic Ph.................. [:=> Show Contents <=:] | |||

## Automatic braking system using fuzzy logicPosted 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 | logic ,
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of directional stability. The system offers the flexibility of setting the separation distance.
Simulation of the controller for driving into a stationary or moving objects shows that the system
is performing well. It also uses an anti lock braking system to decelerate the vehicle and a
throttle on-off controller 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 whethe.................. [:=> Show Contents <=:] | |||

## NEURO FUZZY LOGICPosted 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 | fuzzy logic co2,
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noisy, or missing input information. FL's approach to control problems mimics how a person would
make decisions, only much faster. In the case of fuzzy system, we usually assume the input-output
pairs have the structure of fuzzy if-then rules that relate linguistic of fuzzy variables whose
values are words (fuzzy sets) instead of numbers. Linguistic variables facilitate interpolation by
allowing an approximate match between the input and the antecedents of the rules. Generally, fuzzy
systems work well when we can use experience or introspection to articulate the fuzzy if-then rules.
When we ca..................[:=> Show Contents <=:] | |||

## Automated Eye-Pattern Recognition SystemsPosted 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 | Systems ,
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nates fraudulent authentication and identity privacy and safety controls privileged access or
authorised entry to sensitive sites, data or material. In addition to privacy protection there are
myriad of applications were iris recognition technology can provide protection and security. This
technology offers the potential to unlock major business opportunities by providing high confidence
customer validation. Unlike other measurable 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..................[:=> Show Contents <=:] |

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