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经典的人工智能问题 - iris数据分析问题。通过设计三层bp神经网络对花朵数据进行分类识别，并达到了很好的效果。-classic AI problem - iris data analysis problems. Three-bp through the design of neural networks classify data flower identification, and to achieve good results.
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生物识别：指纹、人脸、虹膜、头骨及静脉识别是最有应用价值的几个，本代码是静脉识别的C++代码，具有极高的参考价值。-Biometrics: fingerprint, face, iris, skull and intravenous application of recognition is the most a few, the vein identification code is C++ code, with a high reference value.
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有导师学习神经网络的分类——鸢尾花种类识别-Supervised learning neural network classification- iris species identification
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We present an iris identification approach based on wavelet-packet binary coding. This latter is carried out by coding the 64 wavelet-packet energies to generate a compact signature
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有导师学习神经网络的分类——鸢尾花种类识别，需要的同学可以下载-Learning from the classification neural network- iris species identification, students need to be downloaded to try
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有导师学习的神经网络分类-鸳尾花种类识别-Supervised learning neural network classifier- iris species identification
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能够实现RBF,GRNN和PNN神经网络的案例，一个是RBF-近红外光谱汽油辛烷值预测，GRNN，PNN-鸢尾花种类识别。代码和数据均有，直接可以拿来使用。(These are cases of RBF, GRNN and PNN neural networks can be realized. One is RBF-NIR spectroscopy gasoline octane prediction, GRNN, PNN-Iris species identification. Both c
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有导师学习神经网络的分类-鸢尾花种类识别(Classification of Instructors Learning Neural Networks - Iris Species Identification)
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