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art模型
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  art 2 model
     The intrusion detection algorithm our used is to learn behavior patterns and to detect anomaly behavior using by a hybrid HMM/ART2 model.
     文中探讨了基于HMM/ART2模型的异常检测方法对操作系统的系统调用序列进行模式识别与异常检测。
短句来源
     The present paper presents a sort of neural net--ART2 model for realizing automatic classification.
     本文提出用一种神经网络———ART2模型来实现自动分类。
短句来源
     ,this paper presents an improved algorithm of ART2 model. The algorithm calculates the relevant vigilance parameter of clustering with reasonable cluster's number through the progresses of self-organizing,iterating and weighting.
     针对经典ART2模型的主观设置警戒参数、输出无组织等不足,提出基于改进算法的ART2模型用于聚类分析;
短句来源
  art-2 network
     Research on Classification of Interim Product Families in Shipbuilding Based on ART-2 Network
     基于ART2模型的造船系统中间产品成组分类研究
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  “art2模型”译为未确定词的双语例句
     Credit Risk Evaluation Based On ART2
     基于ART2模型的信用风险评估
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     still, it can avoid amendment of former study mode of the network. This paper uses ART2 to evaluate credit risk, and its precision and accurateness are prior to other nerve network mode and statistical method through comparative research of real case.
     本文将ART2模型应用于信用风险评估,通过实证比较研究,结果显示应用自适应共振模型进行信用风险评估在精度和准确性上,都优于其他神经网络模型和统计方法。
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  相似匹配句对
     (2) model (n=15), LSD + CsA(15mg. Kg d-1);
     2)模型组:
短句来源
     2. Evaluation model.
     2.评估模型
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     Credit Risk Evaluation Based On ART2
     基于ART2模型的信用风险评估
短句来源
     An Improved ART2 Model by Introducing Forgetting Mechanism
     引入遗忘机制的ART2改进模型
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     The distribution and the thickness of J2(!)
     J2 ( !)
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The ART-Ⅱ model[2] is capable of identifying arbitrary sequence, but, in [2], the dynamical process and self-stability range are not discussed, only the simulation results in different ρ set by author are presented. Based on deeply studying the mechanism of dynamical feedback in ART-Ⅱ, the paper defines the concepts of attractive basin, self-stability, focus point, proposes the algorithm of adaptive ρ. The new mechanism reveals the capability of parallelly searching and continually suiting for the environment...

The ART-Ⅱ model[2] is capable of identifying arbitrary sequence, but, in [2], the dynamical process and self-stability range are not discussed, only the simulation results in different ρ set by author are presented. Based on deeply studying the mechanism of dynamical feedback in ART-Ⅱ, the paper defines the concepts of attractive basin, self-stability, focus point, proposes the algorithm of adaptive ρ. The new mechanism reveals the capability of parallelly searching and continually suiting for the environment changed, and makes the ART-Ⅱ model with adaptive p possess the capability of correcting and tolerating errors in the memory and the certain sensitivity for signal processing, the mechanism overcomes the weakness of original model with fixed p which can cause the error memory. The intelligent system can be formed by integrating the improved model, the digital sampling and reasoning, which realizes the reception of multi-freqaencies in telecommunication system. The result in the test demonstrates that the improved model with adaptive ρ identifies the signal with noise in different degree well.

由文献[2]提出的ART-Ⅱ模型可处理任意序列的辨识问题,但其未涉及网络的动态过程和自稳定区域的研究,只是人工设置不同的ρ值得到仿真结果。本文在深入研究ART-Ⅱ动态反馈机理的基础上,引入了吸引域、自稳定性、聚点等概念,提出了ρ值自适应算法。这一新的机制可以并行搜索和不断地适应外界环境的变化,使得ρ自适应的ART-Ⅱ模型有一定的纠错、容错记忆能力,又有一定的敏感性,克服了原模型ρ值固定时错误记忆的弊病。(由改进型ART-Ⅱ神经网和数据采集、推理机制结合形成一完整智能系统,实现通信系统的多频信号接收处理。系统试验结果表明具有良好的识别效果。

This paper is based on Hamming memory neural network and Adaptive Resonance Theory (ART) model. In theory, we analyzes defects of the Hamming network algorithm. We utilized the idea of ART and developed a fast classification algorithm, called improved hamming algorithm (Im-H Algorithm). This algorithm provides two important properties of updating the thresholds and imtroducing empirical iterations. We have applied this methed to character recognition. A large number of experiments demonstrate its efficiency...

This paper is based on Hamming memory neural network and Adaptive Resonance Theory (ART) model. In theory, we analyzes defects of the Hamming network algorithm. We utilized the idea of ART and developed a fast classification algorithm, called improved hamming algorithm (Im-H Algorithm). This algorithm provides two important properties of updating the thresholds and imtroducing empirical iterations. We have applied this methed to character recognition. A large number of experiments demonstrate its efficiency and its high covergence rate.

本文以海明神经网络与自适应谐振理论(ART)模型学习算法为基础,从理论上分析了海明网络学习算法的缺陷,利用ART网络的思想,提出了一种快速分类的神经元网络的算法,命名为Improved Hamming算法(简称Im-H算法)。此算法主要优点在于阈值更新及引入了经验迭代次数。将此算法用于字符模式识别,大量的计算机实验结果表明了Im-H网络学习算法的有效性、快速性。

It was found recently that the need of ECG in several fields,such as clinic,fundamental research,rehabilitation and special applications in physiology can be met by long-time recording and analyzing of ECG.So the leval of technical requirements for Holter system becomes higher and higher.In this paper, we discuss main requirements for Holter system,including recording part and analyzing part,in order to meet those requirements.We also introduce the principle of using several neural network models to meet technical...

It was found recently that the need of ECG in several fields,such as clinic,fundamental research,rehabilitation and special applications in physiology can be met by long-time recording and analyzing of ECG.So the leval of technical requirements for Holter system becomes higher and higher.In this paper, we discuss main requirements for Holter system,including recording part and analyzing part,in order to meet those requirements.We also introduce the principle of using several neural network models to meet technical requirements for Holter system,including:the use of multilayer perceptron model in data compression and classification;the use of high order neural network model in classifying ECG,and the use of ART model in recognizing T-wave and P-wave of ECG.

为了长时间、准确的记录及分析体表ECG,从各个方面满足基础研究、临床、康复以及特殊生理需要,对Holter系统提出了愈来愈高的要求。作者从技术实现的角度讨论了Holter的主要技术要求,包括记录部分和分析部分;还介绍了几种用神经网络模型满足Holter系统技术要求的原理,包括用多层感知器实现数据压缩及分类,用高阶神经网络实现ECG的分类,以及用ART模型(AdaptiveResonanceTheory)识别ECG中的P波与T波。

 
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