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face recognition RBF neural networks matlab 2002
- 是一个用人工神经网络实现的人脸识别程序,是一个学习人脸识别和神经网络的好东西。 RBF 2002
RBFMatlab
- RBF神经网络用于函数拟合与模式识别的Matlab示例程序-RBF neural network for function approximation and pattern recognition in Matlab Example programs
RBFxunlian
- rbf训练用于模式识别,分类,故障类别的诊断,收敛快-rbf training for pattern recognition, classification, fault type of diagnosis, fast convergence
RbfCharAndNumberTrain
- 基于径向基神经网络的字符和数字的训练,主要用于车牌识别,效果不错-RBF neural network based on the characters and figures of training, mainly used for license plate recognition, good results
NeuralNetwork_RBF_Classification
- MATLAB中应用RBF神经网络对模式识别处理-MATLAB Application of RBF neural networks for pattern recognition processing
RBF
- 基于RBF神经网络的语音识别方法的应用研究-RBF neural network-based speech recognition methods applied research
Mel_RBF
- 基于Mel倒谱特征和RBF网络的孤立词语音识别方法-Mel-based cepstral features and RBF networks isolated word speech recognition method
rbf
- rbf神经网络用于机械故障的诊断,模式识别,分类等-rbf neural networks for machine fault diagnosis, pattern recognition, classification, etc.
fenlei
- rbf神经网络用于分类识别,故障诊断,模式识别,自己编写的-rbf neural network for classification and recognition, fault diagnosis, pattern recognition, have written
handwrittencharacterrecognition
- 三种神经网络方法用于手写体字符识别PNN、RBF、BP-Three kinds of neural networks for handwritten character recognition PNN, RBF, BP
xunorbf
- 用rbf神经网络对经提取得到的信号特征参数进行信号的模式识别。-Rbf neural network by using extracted parameters of the signal characteristics of the signal pattern recognition.
imagerecognition
- it is a image recognition with rbf neural network
RBF-recong
- 使用人工神经元网络RBF对图片进行识别,识别率较高-RBF artificial neural network using the picture identification, recognition rate
RBF
- 人工神经网络 模式识别 对信号进行分类识别 0 1 识别-Artificial neural network pattern recognition to classify the signal recognition 01
RBF
- 径向基神经网络对输入信号进行分类识别,准确度高。-RBF neural network to classify the input signal recognition accuracy.
Wavelet-and-RBF-neural-network
- 利用小波和RBF神经网络进行手写数字识别-Wavelet and RBF neural network handwritten numeral recognition
RBF遗传优化
- RBF网络能够逼近任意的非线性函数,可以处理系统内的难以解析的规律性,具有良好的泛化能力,并有很快的学习收敛速度,已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。(RBF network can approximate any nonlinear function, regularity can handle within the system to parse, has good generalization ability and
RBF
- RBF网络能够逼近任意的非线性函数,可以处理系统内的难以解析的规律性,具有良好的泛化能力,并有很快的学习收敛速度,已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。(RBF network can approximate any nonlinear function, regularity can handle within the system to parse, has good generalization ability and
rbf
- RBF网络能够逼近任意的非线性函数,可以处理系统内的难以解析的规律性,具有良好的泛化能力,并有很快的学习收敛速度,已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。 简单说明一下为什么RBF网络学习收敛得比较快。当网络的一个或多个可调参数(权值或阈值)对任何一个输出都有影响时,这样的网络称为全局逼近网络。由于对于每次输入,网络上的每一个权值都要调整,从而导致全局逼近网络的学习速度很慢。BP网络就是一个典型的例子。(RBF network
RBF
- 基于RBF的手写数字图像识别,matlab程序,欢迎下载交流(Based on RBF handwritten digital image recognition, matlab program, welcome to download and exchange)