连续自适应控制的神经动力系统研究

V. Sudakov, V. Osipov, Y. Nechaev, A. Vasilyev
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引用次数: 0

摘要

提出了一种基于神经动力学系统的动态物体与环境交互行为的控制与预测问题的形式化数学表述。这样的观点使我们能够从系统的立场出发,考虑构建一个多处理器计算机集成复合体的学习环境,一个对复杂动态对象生命周期各阶段进行连续自适应控制的解释性神经动力学系统的概念方案。方法支持的基础是系统分析原理、动态突变理论、神经模糊和神经进化建模的方法和技术,使环境信息和物理实验数据的处理和解释过程形式化,这是基于现代智能技术和高性能计算的成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Study of Neurodynamic Systems of Continuous Adaptive Control
A formal mathematical formulation of the problem of control and prediction of dynamic object behavior in interaction with the environment based on a neurodynamic system was proposed. Such point of view allowed us to consider from the system positions the conceptual schemes of building an integrated complex of multiprocessor computer learning environment of an interpreting neurodynamic system of continuous adaptive control of complex dynamic objects at the stages of their life cycle. The basis of methodological support are the principles of system analysis, dynamic catastrophe theory, methods and technologies of neuro-fuzzy and neuroevolutionary modeling, which allows formalizing the procedures of processing and interpretation of information about the environment and physical experiment data based on the achievements of modern intelligent technologies and high-performance computing.
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