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Image Processing-Based Center Calculation Method for General and Interval Type-2 Fuzzy Systems

机译:基于图像处理的通用和区间2型模糊系统中心计算方法

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摘要

Despite being a good method against uncertainties, the high complexity of the operations in type-2 fuzzy system makes it slow. So, it should be reduced to use type-2, especially in real-time problems. In this study, a method based on image digitization has been proposed for type-reduction and defuzzification steps, which are forming the actual computational complexity in type-2 fuzzy systems. Instead of solutions using iterative and complex methods, the problem is converted into image processing problem by digitizing the fired outputs. The deduction methods such as the center of gravity are computed easily on digitized images. Example scenarios show that the work done is superior to KM algorithm in terms of both precision and computational complexity. In addition, different simulations were conducted to demonstrate the superiority of the study over real problems, and the study was tested for a complex human model motion control problem.
机译:尽管是解决不确定性的好方法,但是2型模糊系统中运算的高复杂性使其运行缓慢。因此,应减少使用type-2,尤其是在实时问题中。在这项研究中,提出了一种基于图像数字化的方法用于类型减少和去模糊步骤,这些步骤正在形成类型2模糊系统中的实际计算复杂性。代替使用迭代和复杂方法的解决方案,该问题通过将激发的输出数字化而转换为图像处理问题。推论方法(例如重心)可以在数字化图像上轻松计算。示例场景表明,在精度和计算复杂度方面,完成的工作均优于KM算法。另外,进行了不同的仿真以证明该研究优于实际问题,并且对该研究进行了针对复杂的人体模型运动控制问题的测试。

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