Iris recognition model based on Curvelet transform and least square support vector machine

2014 ◽  
Author(s):  
Dongrui Li ◽  
Huina Liang
Keyword(s):  
Support Vector Machine ◽  
Iris Recognition ◽  
Curvelet Transform ◽  
Least Square ◽  
Support Vector ◽  
Recognition Model ◽  
Model Based

scholarly journals Parameter-identification investigations on the hysteretic Preisach model improved by the fuzzy least square support vector machine based on adaptive variable chaos immune algorithm

2017 ◽  
Vol 36 (3) ◽  
pp. 227-242 ◽  
Author(s):  
E Jiaqiang ◽  
Cheng Qian ◽  
Hao Zhu ◽  
Qingguo Peng ◽  
Wei Zuo ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Immune Algorithm ◽  
Least Square ◽  
Support Vector ◽  
Preisach Model ◽  
Model Based ◽  
Weight Factors ◽  
Penalty Factor ◽  
Kernel Parameter ◽  
Factor C

In order to solve the hysteretic character of the piezoelectric material for application, the initial weight factors of the hysteretic units are calculated by the Preisach theory and the first-order reversal curves test data, a hysteretic Preisach model based on the improved fuzzy least square support vector machine (improved FLS-SVM) is established. In the established model, the fuzzy least square support vector machine is introduced to calculate more weight factors of the hysteretic units and the adaptive variable chaos immune algorithm is introduced to optimize the penalty factor and the kernel parameter of the FLS-SVM (the penalty factor c = 35 and the kernel parameter σ = 1.35 are obtained). Moreover, the quadratic polynomial interpolation method is used to eliminate the sawtooth phenomenon. The validity of established model reveals that fuzzy least square support vector machine method based on adaptive variable chaos immune algorithm (FLS-SVMAVCIA) is more accurate than FLS-SVM method according to application results of the real actuators (the absolute mean error of the FLS-SVMAVCIA model is less than 1 µm and its maximum error is less than 2 µm). As a result, the hysteretic phenomenon can be effectively eliminated by the hysteretic Preisach model based on the FLS-SVMAVCIA method.

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