The embedded training algorithm is highlighted in this part.
嵌入式训练算法是这部分的重点。
This initializing method can also be used as fast training algorithm for H-MLP network.
该初始化方法同时可作为H-MLP网络的一种快速训练算法。
A novel algebraic training algorithm for a three-layered MLP is proposed in this paper.
本文针对三层前馈网络提出一种全新的学习算法。
The authors introduce the operating principle, network structure and training algorithm.
介绍了工作原理，网络结构和训练算法。
The main deducing steps are presented in the core-training algorithm of text categorization.
对于文本分类的核心训练算法，给出主要步骤的推导过程；
A Complex-valued Functional Link Neural Network (CFLNN) with its training algorithm is proposed.
提出了一种复值函数型连接神经网络(CFLNN)结构及其学习算法。
This paper presents a training algorithm for probabilistic neural networks using the MCE criterion.
提出了一种基于最小分类错误准则的概率神经网络的训练算法。
A structure and training algorithm for quasi-diagonal recurrent neural network (QDRNN) is presented.
提出一种准对角递归神经网络(QDRNN)结构及学习算法。
The scale factor training algorithm has been brought forward to accelerate the training of BP network.
提出了比例系数BP网络训练算法，提高了网络的训练速度。
Analysis the current RBF neural network at the same time do some improve work on its training algorithm.
对现有的RBF神经网络进行了分析，并对训练过程中使用的聚类算法进行了改进。
Now we introduce trajectory model in speaker recognition and improve the codebook training algorithm for VQ.
文章把轨线模型应用于说话人识别，同时对VQ模型的电码本训练算法进行了改进。
Some alteration were made on structure and training algorithm for traditional serial fuzzy BP neural network.
本文对传统的串联型模糊bp网络进行了结构和训练算法上的部分改进。
After analysis of em algorithm, we presented a new cooperative training algorithm based on incremental learning.
本文在分析了EM算法的基础上，提出了一种新的协同训练算法。
The text preprocessing, feature selection, training algorithm, and recognition method are described in the paper.
对文本分类系统的系统结构、预处理、特征提取、训练算法、分类算法等进行了详细介绍。
Describing the type of fuzzy neural network and training algorithm, neural network and fuzzy theory combined forecasting model.
介绍了模糊神经网络的类型和训练算法，将神经网络、模糊理论结合，建立预测模型模型。
The major contributions of the dissertation are stated as follows: 1 a new training algorithm is proposed to obtain RBF centers.
针对R BF训练算法中径向基函数中心确定的困难，在分析比较目前较好的算法基础上，提出一种新的训练算法。
The WAS generally includes the Web page purification, feature selection, vector representation, training algorithm, classification al.
网页自动分类一般包括网页净化、特征选择、向量表示、训练算法、分类算法等五个部分。
This paper presents an efficient training algorithm for probabilistic neural networks using the minimum classification error criterion.
提出了一种基于最小分类错误准则的概率神经网络的训练算法。
Secondly, the hybrid training algorithm is proposed on the base of the Error Back-propagation algorithm's disadvantage analysis in the paper.
其次，从误差反传算法在预测中存在的问题入手，提出一种混合训练算法。
Then an end-point forecast model was built based on the RBF neural network by analyzing the melting technology and the RBF training algorithm.
然后通过对真空感应冶炼工艺机理的深入分析以及对神经网络算法的研究，建立了基于RBF神经网络的终点预报模型。
A new training approach for the training algorithm of a fully connected recurrent neural network based on the digital filter theory is proposed.
一种新的基于数字滤波器理论的全互连复值递归神经网络训练方法被提出。
The method utilizes fuzzy neural network as executive institution of fault diagnosis, and utilizes BP algorithm as training algorithm of network.
该方法采用模糊神经网络融合诊断中心作为故障诊断的执行机构，算法上采用BP算法。
VQ Model Based on Clustering Validity Analysis: it's the flaw for the codebook training algorithm that the size of codebook is choosed artificially.
基于聚类有效性分析的VQ模型：VQ模型电码本的训练算法有一个弱点：电码本大小是人为指定的。
The structure of a partially connected feed forward neural network and the training algorithm based on the recursive prediction error are constructed.
构造了局部连接的前馈神经网络的结构和基于递推预报误差的网络训练算法；
A maximum entropy model of feature extraction for the gas disaster information is established, with the training algorithm of the maximum entropy presented.
以最大熵原理为基础，建立了最大熵瓦斯灾害信息特征提取模型，提出了最大熵模型的参数训练算法。
Through analyzing CDHMM training algorithm, this system is implemented successfully in using high performance float-point DSP TMS320C6711 of TI incorporated.
在分析了CDHMM训练算法运算特性的基础上，采用TI高性能浮点DSP芯片TMS320C 6711成功实现了口令式语音的CDHMM的训练。
BP algorithm is the most popular training algorithm for feed forward neural network learning. But falling into local minimum and slow convergence are its drawbacks.
BP算法是前馈神经网络训练中应用最多的算法，但其具有收敛慢和陷入局部极值的严重缺点。
Adopts a classifier support vector machine which is a very good training algorithm, which can acquire very good generalization when the training datum are very few.
文中采用的分类器——支持向量机是一种能在训练样本数很少的情况下达到很好分类推广能力的学习算法。
Neural network BP training algorithm based on gradient descend technique may lead to entrapment in local optimum so that the network inaccurately classifies input patterns.
基于梯度下降的神经网络训练算法易于陷入局部最小，从而使网络不能对输入模式进行准确分类。
Neural network BP training algorithm based on gradient descend technique may lead to entrapment in local optimum so that the network inaccurately classifies input patterns.
基于梯度下降的神经网络训练算法易于陷入局部最小，从而使网络不能对输入模式进行准确分类。
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