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Handwritten Digit Recognition using Adaptive Neuro-Fuzzy System and Ranked Features

机译:使用自适应神经模糊系统和排名特征的手写的数字识别

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This paper investigates Adaptive Neuro-Fuzzy Inference System (ANFIS) for recognition of handwritten digits. First, an efficient feature extraction module based on five feature extraction techniques has been performed. Second, an optimal feature selection method for feature ranking and feature reduction has been proposed. Third, a classification based on ANFIS has been done. The Experiments has been performed on standard handwritten digit dataset to evaluate the performance of the proposed system. Simulation result revels the proposed system has low testing and checking error with high recognition accuracy.
机译:本文研究了自适应神经模糊推理系统(ANFIS),用于识别手写数字。首先,已经执行了基于五个特征提取技术的有效特征提取模块。其次,已经提出了用于特征排序和特征减少的最佳特征选择方法。第三,已经完成了基于ANFIS的分类。在标准手写数字数据集上进行了实验,以评估所提出的系统的性能。仿真结果陶醉的建议系统具有低识别精度的测试和检查误差。

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