提出了一种粗糙模糊神经网络分类器的模型。
A model of rough fuzzy neural network classifiers is proposed.
特征量被预处理后，输入到集成bP神经网络分类器中分类。
Finally, the features are preprocessed, then classified by integrating BP neural networks.
利用BP神经网络分类器及选择的特征值对缺陷进行了模式分类。
Pattern classification of flaw is carried out with BP neural network and the feature selected.
研究了一种用模糊集表示火箭发动机故障模式的神经网络分类器。
A neural network classifier that utilizes fuzzy sets as failure classes of a liquid propellant rocket engine is studied.
最后，设计神经网络分类器对汉字，字母，数字进行训练和识别。
Finally, design the neural network classifiers in order to train and recognize the character, letters and licenses.
盒维数的简单统计结果可以作为PQ神经网络分类器的输入特征量。
After simple statistics, the dimension can act as the input vector of ANN for PQ classification.
提出了一种用于船舶噪声分类的局域自适应子波神经网络分类方法。
In this paper, an efficient engineering classification of ship noises based on a local adaptive wavelet neural network is presented.
当应用在概率神经网络分类时，可对其固有的两个缺点都有所改善。
When applied to the Probabilistic Neural Networks, the approach improves its two inherent shortcomings.
目前，在脑瘤图像模式识别领域，主要是运用神经网络分类器来做分类识别。
Now, in the fields of the pattern recognition of brain tumor images, the pattern classifications which are used widely are mainly the artificial neural networks classifications.
本文以统计理论为基础，主要讨论在计算机上用软件模拟实现的神经网络分类器。
Based on the theory of statistics, this dissertation investigates neural network classifiers realized with software simulation in the computer.
实验结果表明：算法优化后的神经网络分类器不但学习速度快，还能保证分类精度。
Experiment shows neural network classifier that is optimized by algorithm could not only have fast learning speed but also ensure accuracy of classification.
改进型BP神经网络分类识别系统在遥感图像的自动分类识别上有广阔的应用前景。
The modified BP Nerve Network Classify and Identify System has a very wide application foreground in TM images.
实验表明，基于BP神经网络分类器可以得到较好的结果，正确率可达到88%以上。
It is showed from the experiments that a satisfactory result is achieved from classifiers based on BP neural network, with the accuracy rate more than 88%.
提出了一种新的基于像元信息分解和神经网络分类相结合的城市绿地遥感信息自动提取方法。
A new automatic classification model of remote sensing image using pixel information decomposition combined with neural network classification is proposed in this paper.
该系统采用基于自组织神经网络分类器，其在线分类结果与人工配皮的一致性在84%以上。
The system adopts the neuro-network sorter based on self-organization. The consistence of the on-line sorting result with artificial sorting is above 84%.
提出了一种新的基于像元信息分解和神经网络分类相结合的城市绿地遥感信息自动提取方法。
It can be found that the mixed pixel decomposing is a good method to extract information from the remote sensing images with less spatial resolution.
本文基于学习矢量量化（LVQ）神经网络分类器，实现了舌象分析中的舌色、苔色自动分类。
Tongue color automatic classification, based on LVQ neural networks classifier, is proposed in this paper.
文章从实用、经济和高效的角度出发，提出了一种优化BP神经网络分类器的设计与实现方案。
This paper develops a method to design and perform an optimal BP network classifier, considered with the utility, economy and efficiency of the classifier.
为了验证特征的有效性，使用最近邻及概率神经网络分类器进行了目标识别，得到满意的识别率。
In order to validate character validity, use NearestNeighbor (NN) and probabilistic neural network (PNN) classification identify target, gain content identification probability.
本文对系统中的车牌定位和字符分割、特征提取、BP神经网络分类器等模块进行了较详细的研究。
In this paper, the system of license plate location and character segmentation, feature extraction, BP neural network classifier etc modules have had a more detailed research.
其中自组织神经网络分类器和粒子群优化支持向量机是本文新设计的两种运动想象EEG分类方法。
The self-organizing neural network classifier and particle swarm optimization-support vector machine were designed by author in this paper to use as classification method of motor imagery EEG.
最后，用子空间分类器和BP神经网络分类器构造了一个混联模型，用于手写英文字母和数字的识别。
A mix model with the subspace classifier and BP neural network classifier was realized, which is used in handwritten English letter and number recognition.
用BP人工神经网络分类器进行识别，结果表明矩特征的识别率较高，说明该方法具有良好的应用效果。
The recognition with BP artificial neural net grader shows that the recognition rate of moment features is rather high, this indicates that this method has better applicable effect.
同时，对缺陷的自动分类方法、神经网络分类器和用于对带钢质量进行自动分级的专家系统做了简要介绍。
At the same time, the automatic classification method to the defects, the nerve net classified units, and the experts system to classifying the surface quality were reviewed.
分别采用K -近邻分类器、BP神经网络分类器和SVM分类器进行步态鉴别实验，均获得了较好的鉴别效果。
K-neighbor classifier, BP neural network classifier and SVM classifier are used for gait identification respectively, and all of them obtain good identification results.
该网络从输入语音信号的特征矢量序列中提取出一组固定数目的特征矢量，然后将这特征矢量馈入神经网络分类器进行识别。
It picks up the character vectors of a group of Numbers from the sequence of the character vectors of the input speech signals, and then put the vectors into the NN sorter to recognize.
并且与图像分类中统计方法的经典算法贝叶斯分类方法做了比较，结果发现，神经网络分类方法的分类效果要优于贝叶斯方法。
Comparing with Bayes method-the classical algorithm, we conclude that the neural network is better than Bayes method. This paper gives all the procedures of SAR image classification.
还利用三种飞机缩比模型的暗室测量数据，研究了时延神经网络分类器中时延单元数目对分类精度的影响以及分类器的分类性能。
The effect of time delay unit number on classification precision and the performance of TDNN classifier using three typical aircraft dark room data measured with scale model were studied.
汽车类型自动识别在现代交通管理和监控中有着广阔的应用前景，本文提出一种用于汽车类型识别的BP神经网络分类器的设计问题。
This paper proposes a kind of method of automatic vehicle recognition. The automatic recognition of automobile type has a promising and practical future in the traffic control.
汽车类型自动识别在现代交通管理和监控中有着广阔的应用前景，本文提出一种用于汽车类型识别的BP神经网络分类器的设计问题。
This paper proposes a kind of method of automatic vehicle recognition. The automatic recognition of automobile type has a promising and practical future in the traffic control.
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