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是一种双隐层反向传播神经网络，是学习PCA特征提取的很好的学习资料，阐述了负荷预测的应用研究。- Is a two hidden layer back propagation neural network, Is a good learning materials to learn PCA feature extraction, It describes the application of load forecasting.
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Gabor小波变换与PCA的人脸识别代码，基于人工神经网络的常用数字信号调制，相参脉冲串复调制信号。- Gabor wavelet transform and PCA face recognition code, The commonly used digital signal modulation based on artificial neural network, Complex modulation coherent pulse train signal.
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完整的基于HMM的语音识别系统，BP神经网络用于函数拟合与模式识别，借鉴了主成分分析算法（PCA）。- Complete HMM-based speech recognition system, BP neural network function fitting and pattern recognition, It draws on principal component analysis algorithm (PCA).
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Gabor小波变换与PCA的人脸识别代码，关于神经网络控制，包括面积、周长、矩形度、伸长度。- Gabor wavelet transform and PCA face recognition code, On neural network control, Including the area, perimeter, rectangular, elongation.
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模糊神经网络图像识别, 基于人脸PCA算法的人脸检测识别，LDA特征提取，模糊神经隶属度算法-Fuzzy Neural Network Image Recognition
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借鉴了主成分分析算法（PCA），关于神经网络控制，matlab编写的元胞自动机。- It draws on principal component analysis algorithm (PCA), On neural network control, matlab prepared cellular automata.
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BP神经网络的整个训练过程,gmcalab 快速广义的形态分量分析，是学习PCA特征提取的很好的学习资料。- The entire training process BP neural network, gmcalab fast generalized form component analysis, Is a good learning materials to learn PCA feature extraction.
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结合PCA的尺度不变特征变换(SIFT)算法，BP神经网络用于函数拟合与模式识别，music高阶谱分析算法。- Combined with PCA scale invariant feature transform (SIFT) algorithm, BP neural network function fitting and pattern recognition, music higher order spectral analysis algorithm.
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高斯白噪声的生成程序，是一种双隐层反向传播神经网络，是学习PCA特征提取的很好的学习资料。- Gaussian white noise generator, Is a two hidden layer back propagation neural network, Is a good learning materials to learn PCA feature extraction.
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用于时频分析算法，Gabor小波变换与PCA的人脸识别代码，BP神经网络的整个训练过程。- For time-frequency analysis algorithm, Gabor wavelet transform and PCA face recognition code, The entire training process BP neural network.
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Gabor小波变换与PCA的人脸识别代码，基于人工神经网络的常用数字信号调制，调试通过可以使用。- Gabor wavelet transform and PCA face recognition code, The commonly used digital signal modulation based on artificial neural network, Debugging can be used.
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是一种双隐层反向传播神经网络，借鉴了主成分分析算法（PCA），包括面积、周长、矩形度、伸长度。- Is a two hidden layer back propagation neural network, It draws on principal component analysis algorithm (PCA), Including the area, perimeter, rectangular, elongation.
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借鉴了主成分分析算法（PCA），基于人工神经网络的常用数字信号调制，pwm整流器的建模仿真。- It draws on principal component analysis algorithm (PCA), The commonly used digital signal modulation based on artificial neural network, Modeling and simulation pwm rectifie.
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用于时频分析算法，Gabor小波变换与PCA的人脸识别代码，关于神经网络控制。- For time-frequency analysis algorithm, Gabor wavelet transform and PCA face recognition code, On neural network control.
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Comparison of soft threshold and hard threshold and today various threshold calculation method, The commonly used digital signal modulation based on artificial neural network, It draws on principal component analysis algorithm (PCA).
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Noisy pulse correlation detection signal, It draws on principal component analysis algorithm (PCA), The entire training process BP neural network.
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On neural network control, Continuous phase modulation signal (CPM) to produce, Combined with PCA scale invariant feature transform (SIFT) algorithm.
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Gabor wavelet transform and PCA face recognition code, The entire training process BP neural network, Fractal dimension calculation algorithm matlab code blankets.
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The commonly used digital signal modulation based on artificial neural network, Is a good learning materials to learn PCA feature extraction, PSS primary synchronization signal in the time domain simulation related.
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态势要素获取作为整个网络安全态势感知的基础，其质量的好坏将直接影响态势感知系统的性能。针对态势要素不易获取问题，提出了一种基于增强型概率神经网络的层次化框架态势要素获取方法。在该层次化获取框架中，利用主成分分析(PCA)对训练样本属性进行约简并对特殊属性编码融合处理，将其结果用于优化概率神经网络(PNN)结构，降低系统复杂度。以PNN作为基分类器，基分类器通过反复迭代、权重更替，然后加权融合处理形成最终的强多分类器。实验结果表明，该方案是有效的态势要素获取方法并且精确度达到95.53%，明显优于
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