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FPGA Synthesis of SIRM Fuzzy System-Classification of Diabetic Epilepsy Risk Levels from EEG Signal Parameters and CBF

机译:FPGA合成SIRM模糊系统 - 患EEG信号参数和CBF的糖尿病癫痫风险水平的分类

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Now a day the epilepsy risk level classification is one of the most important thing in diabetic patient's treatment. That risk level classification is proposed in this paper. SIRM fuzzy processor is synthesized through the FPGA. FUZZY rules are the best way to deal with natural conditions. In this paper epilepsy classification is performed through minimum no of rules. Cerebral blood flow level and EEG signals are used as input parameters. SIRM fuzzy processor with the tuned and untuned conditions is checked for various input values. The better the fuzzy system is identified based on performance and quality values. The tuned SIRM system with five rules is selected which has the performance of 98.58 % and quality value of 36.56. The SIRM system is simulates through VHDL and synthesized by FPGA which has performance value of 98.28. This SIRM fuzzy model is compared with other techniques like homogeneous system, heterogeneous system.
机译:现在,癫痫风险水平分类是糖尿病患者治疗中最重要的事情之一。本文提出了风险级别分类。 SIRM模糊处理器通过FPGA合成。模糊规则是处理自然条件的最佳方式。在本文中,癫痫分类是通过最小规则进行的。脑血流水平和EEG信号用作输入参数。针对各种输入值检查具有调谐和未调谐条件的SIRM模糊处理器。基于性能和质量值识别模糊系统越好。选择具有五种规则的调谐SIRM系统,其性能为98.58%,质量值36.56。 SIRM系统通过VHDL模拟,并由FPGA合成,具有98.28的性能值。该SIRM模糊模型与均匀系统,异构系统等其他技术进行了比较。

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