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作 者:王建平[1] 王光新 李帷韬[1] 宋程楠 WANG Jian-ping;WANG Guang-xin;LI Wei-tao;SONG Cheng-nan(School of Electrical Engineering and Automation,Hefei University of Technology,Hefei 230009,China)
机构地区:[1]合肥工业大学电气与自动化工程学院,合肥230009
出 处:《控制工程》2019年第3期476-483,共8页Control Engineering of China
基 金:国家青年自然科学基金项目(61305029);博士后科学基金面上资助项目(2013M541820);中央高校基本科研业务费专项资金资助项目(2013HGBH0010;2013HGQC0012);安徽省青年自然科学基金项目(1408085QF133)
摘 要:针对已有认知模型面对不同样本采用相同认知需求和固定双树复小波变换(Dual-Tree Complex Wavelet Transform,DTCWT)特征空间的缺陷,仿人面对不同认知需求时自适应调节特征空间反复推敲比对的认知特点,探索一种具有仿反馈调节机制的脱机手写体汉字智能认知模型。首先,提出了一种具有仿反馈调节机制的智能认知模型;第二,分析脱机手写体汉字样本的认知需求,构建不同认知需求下的优化DTCWT特征子空间与分类认知准则;第三,定义认知结果评价准则,通过分析未认知样本的认知需求,自适应调节新认知需求下优化特征子空间和分类认知准则,集成多认知需求下的优化特征子空间构建优化压缩DTCWT特征空间。对GB2312-80手写体汉字样本库进行仿真实验,实验结果表明该方法的优越性。For the drawbacks of existing cognitive models with same cognitive demanding and constant feature space constructed by DTCWT for various samples, an intelligent off-line handwritten Chinese character cognitive model with simulated feedback adjustment mechanism is explored in this paper, to simulate the human cognitive process of the adaptive adjusting feature space to repeat intercomparison and deliberately refine with various cognitive demanding. Firstly, an intelligent cognitive model with simulated feedback adjustment mechanism is proposed. Secondly, the cognitive demanding of samples is analyzed to establish the optimized DTCWT feature subspace and classified cognitive rules for various sample cognitive demanding.Thirdly, the evaluation criteria of cognitive results is defined to adaptively adjust the optimized feature subspace and classified cognitive rules based on the new cognitive demanding from the falsely cognitive samples. The optimized compact DTCWT feature space is established by integrating various optimized feature subspaces of multi-cognitive demanding. The experimental results based on GB2312-80 handwritten Chinese sample library show the superiority of our method.
关 键 词:脱机手写体汉字认知 认知需求 智能认知 仿反馈 双树复小波变换
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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