Kolmogorov networks and process characteristic input-output modes decomposition
Kolmogorov networks and process characteristic input-output modes decomposition
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DOI：
10.1109/is.2002.1044229
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发表时间：
2002-12
期刊：
影响因子：
--
通讯作者：
G. Dimirovski;Yuanwei Jing
中科院分区：
文献类型：
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作者：
G. Dimirovski;Yuanwei Jing
在过去的几十年里，通过数学分析和计算智能的方法开发了表示模型。这种对系统科学的挑战还在继续，因为它本质上涉及数学近似理论。最近，一项从时间域的投入产出角度进行的对比研究已经展开。也就是说，复杂MIMO热工过程的解析分解表示相对于基于Kolmogorov定理的神经网络近似表示。给出了这项研究的主要发现。这些提供了一种新的见解，并突出了相当简单的工业数字控制的效率和健壮性，这些控制是过去设计和实现的，继承了所采用的模型近似。
In the past decades, representation models have been developed both via math-analytical and computational-intelligence approaches. This challenge to system sciences goes on because it involves essentially the mathematical approximation theory. Recently a comparison study via the input-output view in the time domain has been carried out. That is, an analytical decomposition representation of complex MIMO thermal processes relative to the neural-network approximation representations based on Kolmogorov's theorem. The main findings resulting out of this study are presented. These provide a novel insight as well as highlight the efficiency and robustness of fairly simple industrial digital controls, designed and implemented in the past, inherited from model approximation employed.