| 引用本文: | 西广成.智能控制与相对熵最小化[J].控制理论与应用,1999,16(1):27~31.[点击复制] |
| Xi Guangcheng.Intelligrnt Control with Relative Entropy Minimizing[J].Control Theory and Technology,1999,16(1):27~31.[点击复制] |
|
| 智能控制与相对熵最小化 |
| Intelligrnt Control with Relative Entropy Minimizing |
| 摘要点击 1252 全文点击 401 投稿时间：1996-03-25 修订日期：1997-08-25 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 |
| 1999,16(1):27-31 |
| 中文关键词 智能控制 相对熵 IPDI原理 学习功能 记忆功能 归纳功能 |
| 英文关键词 intelligent control relative entropy principle of IPDI function of learning function of assaciative memory function of induction |
| 基金项目 |
|
| 中文摘要 |
| 根据神经行为学和认知心理学观点提出智能控制系统的新构型，从相对熵最小化原理构建智能控制理论。从神经生理学和神经网络理论证明分层控制系统的基本原理IPDI（Increasing ptrcision with decreasing intelligence）,从相对熵最小化观点和IPDI原理出发，讨论智能系统的智能行为，给出关于智能系统学习过程的几个定理和学习算法。 |
| 英文摘要 |
| Based on the point of view of neuroethology and cognition-psychology,a new configuration of intelligent control system is presented in this paper;the theory of intelligent control is constrol is constructed by principle of minimizing of relstvie entropy.The baduc principle of hierarchical intelligent control(IPDI-Increasing precising precision wuth decreasing intelligence)is probed from points of the neutophysiology and the theory of neural network.Intelligent system is discussed from the viewpoint of minimzing of relative entropy and from the prinple of IPDI;several theorems and algorithms for the learning process of intelligent system are given in this paper. |