• Based on the learning characteristic of neural network and the function approximation ability of the wavelet, a new self tuning control algorithm is presented.

    依据小波的非线性逼近能力和神经网络的自学习特性,提出了一种基于小波神经网络模型的自校正控制算法。

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  • Especially to threshold de-noising, a method based on orthogonal wavelet analysis and self-adaptive learning algorithm was proposed here.

    特别是对阈值去噪方法,提出了一种基于正交小波变换和自适应学习算法的噪声抑制方法。

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  • Based on expatiated the basic structure model and some general improved algorithms of BP neural network, this paper brings forward a new self-organization learning algorithm.

    介绍了BP网络的基本结构模型与常见改进算法,在此基础上提出了一种新型的结构自组织BP网络算法。

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  • According to a learning algorithm of self organizing neural network for mapping character, a CMOS implementation of its synaptic weight by circuit is presented in this paper.

    本文根据自组织特征映射神经网络学习算法,提出了其权值的CMOS实现电路。

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  • This model adopts the improved Relevance Verifier algorithm, which not only improves the accuracy of matching, but also solves the self-learning problem.

    该模型采用改进的关联决策算法,使得系统不但提高了准确率,而且还解决了自我学习问题。

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  • As for it, by improving learning algorithm of traditional RBF neural network, a new dynamic cluster-based self-generated method for hidden layer nodes is proposed.

    对此,本文改进了R BF神经网络的学习算法,提出了一种基于聚类的动态自生成隐含层节点的思想。

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  • A self learning fuzzy control algorithm is presented in this paper. The algorithm with a simplified fuzzy relation can save computation.

    本文通过简化模糊控制算法中的模糊关系,建立了一种运算量少,易于实现实时控制的自学习模糊控制算法。

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  • A new statistical algorithm for on line maintenance of knowledgebase has been presented. It is of self learning and able to update the knowledgebase of real time expert system.

    提出一种知识库在线维护的统计算法,用于过程的在线机器自动学习维护。

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  • The paper introduces an on-line self-learning optimization algorithm , and its application on the catalytic cracking process.

    本文介绍一种在线的自学习经验调优系统及其在催化裂化装置的应用。

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  • A new type of adaptive PID controller using diagonal recurrent neural network (DRNN) is presented. An on-line learning algorithm based on PID parameter self-tuning method is given.

    提出了一种基于对角回归神经网络的PID控制器结构,给出了PID参数在线自整定的学习控制算法。

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  • In this paper, introduces a new method of GAL algorithm that can process the sound signal of armored vehicle and improves GAL network based on self-learning.

    介绍了利用GAL算法对装备产生的声音信号进行处理,改进完善了基于竞争学习的GAL神经网络。

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  • The neuron controller with its self-learning ability can realize the on-line learning algorithm, and it is adopted as the position controller of the AC servo system.

    利用神经元的自学习功能实现神经元控制器的在线学习,并以神经元控制器作为交流伺服系统的位置调节器;

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  • After training with a proper learning algorithm, NN has a capability of self-learning, adapting and organizing.

    通过利用合理的学习算法进行训练,神经网络对事物和环境具有很强的自学习、自适应和自组织能力。

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  • The paper introduces a method to identify well logging facies using self organization neural network, which is a non-supervisor learning algorithm.

    作者在本文中介绍了一种利用自组织神经网络进行测井相识别的方法。

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  • In this paper, a self-learning algorithm is put forward based on pricing principle of ASPEN, a microsimulation model of the economy.

    本文根据经济微观仿真模型ASPEN的定价机理,提出了一种自动学习算法。

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  • Simultaneously, if the system temperature is in a temporary state of stability, perfects the parameter U0 based on the self-learning algorithm.

    同时不断判断系统温度是否处于暂时稳定状态,如果是,则启动自学习算法,对U0进行修正。

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  • Based on a neural network and the fuzzy control theory, this paper presents a self-organizing fuzzy-neural network for nonlinear systems, and develops a new learning algorithm.

    基于人工神经网络与模糊控制理论,对非线性系统提出了一种自组织模糊神经网络模型,并推导出一类新型学习算法。

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  • Since the fuzzy observer has a strong subjectivity in fuzzy control rules, self-learning fuzzy velocity observer is produced to present detailed algorithm process.

    由于模糊观测器的模糊控制规则主观性较强,因此设计自学习模糊速度观测器,并给出了详细的算法和流程。

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  • A parameter self-learning algorithm is presented after defining data structure and variable array to improve the prototype's adaptability to different size of workpieces.

    在定义了数据结构和变量数组的基础上,给出了参数自学习过程算法,改善了模型样机对不同规格样本工件的适应性。

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  • An active noise self-tuning model predictive control approach is derived. An on-line learning algorithm is proposed for adjusting the uncertain model parameters.

    将预测控制方法应用到有源噪声控制领域,给出了一种参数在线自适应算法,该算法的收敛速度不受次级声路径响应的影响。

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  • An active noise self-tuning model predictive control approach is derived. An on-line learning algorithm is proposed for adjusting the uncertain model parameters.

    将预测控制方法应用到有源噪声控制领域,给出了一种参数在线自适应算法,该算法的收敛速度不受次级声路径响应的影响。

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