Biological Immune is a highly complexity and self-adaptive system with capability of learning, memory acquisition, pattern recognition and so on.
生物免疫是一个高度复杂的自适应系统，具有学习、记忆和模式识别的能力。
An adaptive neuron control method is presented. By use of this kind of controller, an intelligent control system is designed, and its learning rules are also presented.
该文给出了一种自适应神经元的控制方法，设计了神经元网络作为控制器的智能控制系统，给出了学习规则。
System identification plays an important role in high performance automation technologies such as adaptive control and learning control.
系统辨识是高性能自动化技术(如适应控制与学习控制)中的重要内容。
This paper presents a class adaptive pole assignment control of servo systems based on neural state estimation and develops the system structure and the weight learning algorithms.
提出了一类基于神经元状态估计器的自适应广义极点配置控制，研究了该控制系统的网络结构和权值学习方法。
The system is adaptive and self - learning. Simulation results verify that it's performance is satisfied.
该系统自适应自学习能力强，仿真研究表明，控制效果良好。
The paper presents a new adaptive control system based on PID-like neural network, gives the learning algorithm of this new controller and analyses stability of the control system.
本文提出了一种新的基于PID型神经网络的自适应控制系统，给出了神经网络控制器的学习算法和控制系统的稳定性分析。
The paper proposes an online teaching system based on IRT, and by this system, the managing and tracing process of adaptive learning are realized.
提出将IRT的相关算法应用于在线教学系统，通过相应的算法，实现自适应学习管理和跟踪。
The author conducted an analysis of learning style research, and envisioned an adaptive learning system.
并且试着设计了一份基于这个学习风格三维模型的量表。
The algorithm and the learning rule of the neuron adaptive PID controller for pulp consistency control system are described in this paper.
莲花山造纸厂采用一套新的纸浆浓度和流量测控系统，本文介绍应用该系统的结果。
The algorithm and the learning rule of the neuron adaptive PID controller for pulp consistency control system are described in this paper.
莲花山造纸厂采用一套新的纸浆浓度和流量测控系统，本文介绍应用该系统的结果。
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