The efficiency of artificial neuron is promoted and a new model of artificial is created by studying the learning algorithm.
通过研究神经元学习算法，提高神经元的学习效率，并且提出一种新的神经元模型。
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。
The learning algorithm and the characteristics of the fuzzy rules model which can approximate the experiment data are shown to converge to any arbitrary accuracy by the theoretical analysis.
理论分析说明这种模糊规则后件参数学习算法是收敛的、所建模糊模型能够以要求的精度逼近已知的实验数据。
This paper presents a new method for dynamic model identification of sensors, and gives the corresponding design processes and learning algorithm.
提出了一种传感器动态模型辩识新方法，给出了相应的辩识过程及学习算法。
The general form of CUSI neuron model and its learning algorithm are given, and apply it to geological data analysis and get the better effect than linear regression.
提出了CUSI神经元模型的一般形式，给出其学习算法。通过实例将CUSI神经元模型应用到地质数据的分析上，取得了比线性回归更好的效果。
Linear noise canceller based on TDNN was proposed, and its model, learning algorithm and universal approximation were discussed.
提出基于TDNN神经网络的线性噪声消除器，讨论了它的模型与学习算法及其通用逼近性。
A learning algorithm based on Lyapunov stability is derived to fuzzy relational model identification in this paper.
本文在李雅普·诺夫稳定性意义下，提出了一种辨识模糊关系模型的学习算法。
PN model, LAC neural network and its learning algorithm are all put forward first time in this thesis.
PN神经元模型、lac神经网络及学习算法，都是本文首次提出的。
It established the model's output mathematic function and learning algorithm. Computer simulations showed the equivalence of fuzzy chaos neural network model and the original chaotic system.
确定了模型的输出函数，并推导了模型的学习算法，仿真结果表明永磁同步电机的模糊混沌神经网络模型与原系统是等价的。
This paper presents a model for identifying induction motor speed using the recurrent neural network, which is trained by a real time recurrent learning algorithm.
本文利用递归神经网络来建立异步电机转速辩识模型，其网络学习采用实时递归学习算法。
The learning algorithm is given, and the effectiveness of the model and algorithm is proved by tertiary oil recovery process simulation of oil reservoir development.
文中给出了学习算法，并以油藏开发三次采油过程模拟为例验证了模型和算法的有效性。
The model was a Feedforward Fuzzy neural network possessing five layers, and Gradient Descent was adopted as learning algorithm.
该模型采用五层前向模糊神经网络，学习算法为梯度下降法。
Therefore, based on simulated annealing algorithm, an improved method of game learning was given and a game learning model about oligarch holding the market was established.
基于模拟退火算法，给出了博弈学习的一个改进方法，建立了寡头垄断市场的博弈学习模型。
This paper's main works is that: learning algorithm studies of support vector machine, mathematical model and application about feature selection, convergence analysis of clustering algorithm.
本文主要致力于支持向量机、近似支持向量机的学习算法研究，特征提取的数学模型与算法的改进及其应用，聚类分析算法的收敛性证明。
The results show that this algorithm can model input and output learning kernel of dynamic nonlinear system quickly, which is superior to other learning methods of wavelet network.
结果表明该算法能够对动态非线性系统的输入输出快速学习和建模，优于其它小波网络的学习算法。
In this paper, by analyzing the functional network, a new model and learning algorithm of the serial functional networks is proposed.
通过对泛函网络的分析，提出了一种序列泛函网络模型及学习算法，而网络的泛函参数利用梯度下降法来进行学习。
The algorithm combines active learning, biased classification and incremental learning to model the small sample biased learning problem in relevance feedback process.
该算法将主动式学习、有偏分类和增量学习结合起来，对相关反馈过程中的小样本有偏学习问题进行建模。
Finally, taking data from CAE as samples; the BP neural network of warping-shrinkage prediction model is established by designing the network structure and selection of learning algorithm.
最后以数值仿真得到的数据为样本数据，通过设计网络结构和选用学习算法，建立并得到基于BP人工神经网络的翘曲——收缩预测模型。
A mixed NN model is constructed using BP algorithm improved with dynamic learning rate.
利用动态学习率改进BP算法，建立了混合神经网络模型。
Finally, experimental results of two typical benchmarks demonstrate that the new model and its learning algorithm are feasible and efficient.
两个典型算例的实验结果表明，该模型及其学习算法是可行和有效的。
BP algorithm has aptitude and auto-learning characters, so my paper choose BP neural net algorithm to set up mail classification and recognition model.
BP算法具有智能性和自学习性的特点，因此，本文提出采用BP神经网络来构造邮件分类识别器。
For learning document classification on line, the paper gives the semi-supervised learning fuzzy ART model (SLFART) based on adaptive resonance theory and the models algorithm.
为了对在线学习文档进行分类，本文根据自适应谐振理论给出了一个半监督学习模糊art模型(SLFART)及其算法。
The Word Sense Disambiguation (WSD) study based on large scale real world corpus is performed using an unsupervised learning algorithm based on DGA improved Bayesian Model.
采用基于依存分析改进贝叶斯网络的无指导的机器学习方法对汉语大规模真实文本进行词义消歧实验。
A design method of ahead masking associative memory model with expecting fault-tolerant field is proposed by use of the general feed-forward network and sequential learning algorithm given by authors.
文中用作者提出的通用前馈网络和排序学习算法，提出了一种设计具有期望容错域的前向掩蔽联想记忆模型的方法。
The structure and algorithm of artificial neural network model were described, and the model and learning-procedure of mechanical fault diagnosis neural network were designed.
阐述了人工神经网络模型的一般结构和算法，并设计了机械故障诊断神经网络的模型和学习过程。
A diesel engine fault diagnosis model based on three-layer BP network is put forward, an step-changing learning algorithm based on gold-segmentation is given.
提出了一种基于三层BP网络的柴油机故障诊断模型，给出了一种基于黄金分割法的变步长学习算法。
This paper is concerned with an assessment model of air environmental quality by using fuzzy neural network with multi criteria learning algorithm.
研究了基于多准则学习的模糊神经网络评价环境大气质量的模型。
This paper is concerned with an assessment model of air environmental quality by using fuzzy neural network with multi criteria learning algorithm.
研究了基于多准则学习的模糊神经网络评价环境大气质量的模型。
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