An improved BP neural network classifier is used to recognize CD4 cell images in this paper.
采用改进的BP网络分类器对CD 4细胞图像进行识别。
A model of rough fuzzy neural network classifier was presented by combining rough set and fuzzy neural network.
结合粗糙集和模糊神经网络提出了一种粗糙模糊神经网络识别器的模型。
This paper presents a multiclass neural network classifier to learn disjunctive fuzzy information in the feature space.
本篇论文提出一个类神经网路分类器来学习多类的分离模糊资讯。
A neural network classifier that utilizes fuzzy sets as failure classes of a liquid propellant rocket engine is studied.
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 mix model with the subspace classifier and BP neural network classifier was realized, which is used in handwritten English letter and number recognition.
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。
Usually image recognition based on neural networks needs feature extraction, and then the features extracted are delivered to the neural network classifier.
神经网络用于图像识别一般都要提取图像特征，然后把提取好的图像特征送入神经网络识别器进行识别。
Experiment shows neural network classifier that is optimized by algorithm could not only have fast learning speed but also ensure accuracy of classification.
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。
SFAM is an incremental neural network classifier. It is a simple and fast version of Fuzzy ARTMAP (FAM). Both FAM and SFAM produce the same output given the same input.
SFAM是一个改进版神经网络分离器，是模糊ARTMAP的简化和快速版本。对于相同的输入FAM和SFAM具有相同的输出。
K-neighbor classifier, BP neural network classifier and SVM classifier are used for gait identification respectively, and all of them obtain good identification results.
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。
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.
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。
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.
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。
BP neural network based on sensitivity analysis is used as base classifier to learn the subsets and redundant genes are further removed.
采用基于灵敏度分析的BP神经网络模型作为基分类器，进一步剔除冗余基因。
Checked by the experiments, the improved RBF network has less hidden neural units than before, at the same time keep the accurate of RBF based classifier.
经实验证明，基于改进后的RBF网络具有更少的隐含神经元，但仍然保持了基于RBF网络分类器的准确率。
In this paper, considering the features of remote sensing images, we proposed a remote sensing image classifier using radial basis function neural network.
针对遥感图象分类的特点，提出了一种径向基函数神经网络的遥感图象分类器。
Here, the HMM is employed to produce a best speech state sequence which is warped to a fixed dimension vector and the RBF neural network is used as classifier.
该方法首先利用HMM生成最佳语音状态序列，然后用函数逼近技术产生对最佳状态序列进行时间规正，最后通过RBF神经网络进行分类识别。
A combined classifier is designed. There are two recognition ways used in the classifier. They are the least distance pattern recognition method and the BP neural network pattern recognition method.
设计了一个二级组合分类器，该分类器综合使用了最小距离和BP神经网络两种模式识别方法。
These features are used to train a B-P neural network, it is a classifier and can improve greatly the recognition rate of Chinese characters.
使用该B-P神经网络作为汉字的分类器，可以大大提高车牌汉字的识别率。
It extracted eigenvalues from pretreated medical images, and then classified medical images by using classifier based on improved wavelet neural network algorithm.
将经过预处理的医学图像提取特征值，然后利用基于改进的小波神经网络算法的分类器对医学图像进行分类。
An intelligent pattern classifier with B-P neural network is used in recognition of those five kinds of AE signals successfully.
采用B - P型反向传播神经网络构成的智能化模式分类器，对此五类声发射信号进行识别，获得了满意的效果。
Then, combining IMD-Isomap and generalized regression neural network, which has a good ability for approximation, a classifier is proposed.
然后，结合泛化回归神经网络，设计出一种分类器。
The manual neural network has become more and more important as a classifier. Learning from the environment adaptively and generalizing were the most advantages of neural network.
人工神经网络日渐成为一种重要的分类工具，其最大益处就在于它善于对环境的自适应学习，并且具有并行处理泛化能力。
The third part of paper discusses the design of neural network group classifier, in view of speciality of vehicle recognition, neural network algorithms are applied to resolve the problem.
本文第三部分讨论了神经网络分类器的设计鉴于汽车识别问题的特性，充分利用神经网络的并行分布处理的特点，将神经网络算法用于汽车识别。
The BP neural network is used as classifier.
采用BP神经网络实现分类器。
First selects texture features based on the gray level co-occurrence Matrix and then EBP-OP neural network is used as a classifier. The experimental results show that this method is very effective.
首先运用灰度共生矩阵提取图像的纹理特征，然后用EBP - OP算法对提取的纹理特征进行分类，并在此基础上实现一组纹理图像的检索，实验证明这种方法是有效的。
First selects texture features based on the gray level co-occurrence Matrix and then EBP-OP neural network is used as a classifier. The experimental results show that this method is very effective.
首先运用灰度共生矩阵提取图像的纹理特征，然后用EBP - OP算法对提取的纹理特征进行分类，并在此基础上实现一组纹理图像的检索，实验证明这种方法是有效的。
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