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神经网络学习中的矢量量化算法，VC编写完整源代码，很有参考价值。-neural network learning vector quantization algorithm, the preparation of VC source code integrity, of great reference value.
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MATLAB中应用支持向量肌（SVN）神经网络对模式识别处理-MATLAB Application of Support Vector muscle (SVN) neural network for pattern recognition processing
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能够实现支持向量机的界面操作，支持向量机比神经网络功能强大，能够实现分类和识别-Support vector machine (SVM) to realize the interface operation, support vector machine (SVM) is a powerful than neural network, which can achieve the classification and recognition
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Support Vector Neural Network (SVNN)
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生成8类数据点，神经网络对数据点分类 求解权向量-8 classes generated data points, solving the weight vector neural network data points classification
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多维支持向量机 可以解决小样本情况下的机器学习问题。可以提高泛化性能。可以解决高维问题。可以解决非线性问题。可以避免神经网络结构选择和局部极小点问题。-Multidimensional support vector machine can solve the problem of machine learning small sample case. You can improve the generalization performance. You can solve high-dimens
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