This article describes a new type of fuzzy system with interpolating capability to extract MISO fuzzy rules from input output sample data through learning.
描述了一个通过学习从输入输出采样数据中提取MISO模糊规则的具有插值性能的新型模糊系统。
The input and output use the standard rectangle wave-guide, the transition between rectangle wave-guide and fin-line is continuous gradual change line, and it has good capability of matching.
开关的输入、输出使用标准矩形波导，鳍线和矩形波导之间采用连续渐变线进行过渡，匹配性能良好。
Observability is the capability of the test system to observe the output of the IUT and to determine which input triggers the particular output.
可观察性是指测试系统观察iut的输出、判断输入与输出对应关系的能力。
In this model, the continuous input-output mapping of the system is realized by nonlinear mapping capability to the time variable of process neural networks.
该模型利用过程神经元网络所具有的对时间变量的非线性映射能力，实现系统的输入、输出之间的连续映射关系。
In addition, compared with high non-linear auditory system, artificial neural network has the capability to learn from limit sample sets and map input to output in various dimensions.
并且，对于高度非线性的听觉系统，采用从有限的实际样本中“自学习”到具有输入输出关系能力的人工神经网络模型来实现。
In addition, compared with high non-linear auditory system, artificial neural network has the capability to learn from limit sample sets and map input to output in various dimensions.
并且，对于高度非线性的听觉系统，采用从有限的实际样本中“自学习”到具有输入输出关系能力的人工神经网络模型来实现。
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