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DICTA
2007

Fuzzy Model Based Recognition of Handwritten Hindi Characters

13 years 5 months ago
Fuzzy Model Based Recognition of Handwritten Hindi Characters
This paper presents the recognition of handwritten Hindi Characters based on the modified exponential membership function fitted to the fuzzy sets derived from features consisting of normalized distances obtained using the Box approach. The exponential membership function is modified by two structural parameters that are estimated by optimizing an objective function that includes the entropy and error function. A Reuse Policy that provides guidance from the past policies is utilized to improve the reinforcement learning. This relies on the past errors exploiting the past policies. The Reuse Policy improves the speed of convergence of the learning process over the strategies that learn without reuse and combined with the use of the reinforcement learning, there is a 25-fold improvement in training. Experimentation is carried out on a database of 4750 samples. The overall recognition rate is found to be 90.65%.
Madasu Hanmandlu, O. V. Ramana Murthy, Vamsi Krish
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where DICTA
Authors Madasu Hanmandlu, O. V. Ramana Murthy, Vamsi Krishna Madasu
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