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自组织神经网络,用于模式识别以及故障智能诊断。
-self-organizing neural networks for pattern recognition and intelligent fault diagnosis.
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神经网络识别人脸。包含说明文件。可对不同人的不同姿态的摄影图像进行分类。-neural network recognition face. Includes note. To be different people different posture photographic image classification.
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对具有随机噪声的二阶系统的模型辨识，进行标幺化以后系统的参考模型差分方程为： y(k)=a1*y(k-1)+a2*y(k-2)+b*u(k-1)+s(k) 式中，a1=0.3366,a2=0.6634,b=0.68,s(k)为随机噪声。由于神经网络的输出最大为1，所以，被辨识的系统应先标幺化，这里标幺化系数为5。采用正向建模(并联辨识)结构，神经网络选用3-9-9-1型，即输入层i，隐层j包括2级，输出层k的节点个数分别为3、9、9、1个；由于神经网络的最大输出为1，因此在辨识前应对原系统参考模
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模式识别入门与提高（代码大全）包括很多实例，尤其是神经元网络-entry and improve pattern recognition (code Daquan) includes many examples, in particular neural network
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C#使用神经网络实现光学字符识别(OCR)源代码-Csharp use the neural network optical character recognition (OCR) the source code
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Neural Network OCR.
There are many different approaches to optical character recognition problem. One of the most common and popular approaches is based on neural networks, which can be applied to different tasks, such as pattern recognition, time
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This my first implementation of gradient descent algorithm in which I will write about the evolution of neural networks. I will start with the most simple network of all, the Single Layer Perceptron, and work through different architectures and learn
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BP神经网络实现字符的识别，从最开始的车牌定位到最终通过神经网络实现字符的识别。-BP neural network character recognition, license plate positioning from the beginning to the final neural network character recognition.
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用C#编写，使用神经网络识别鼠标手势，抛砖引玉-using C# and neural network to recognition mouse signal
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用C#实现车牌识别系统，采用了bp神经网络的训练方法-With C# license plate recognition system, using a neural network training methods bp
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车牌识别算法，采用BP神经网络的方法进行车牌字符识别，并能把汉字识别出来。-License plate recognition algorithm, using the BP neural network method for license plate character recognition, and to recognize Chinese characters.
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基于SVM与人工神经网络的车牌识别算法，使用了OpenCV的图像处理函数，在VS2013 + OpenCV 2.4.9平台上实现-SVM algorithm based on license plate recognition and artificial neural network, using OpenCV image processing function, implemented on VS2013+ OpenCV 2.4.9 platform
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