PCA主元分析后用神经网络预测，A/S含量，PCA算法实现，与神经网络-PCA principal component analysis using neural network prediction, A/S content, PCA algorithm, and neural network

We propose an algorithm for facial expression recognition which can classify the given image into one of the seven basic facial expression categories (happiness, sadness, fear, surprise, anger, disgust and neutral). PCA is used for dimensionality red

利用matlab写成的窄带噪声发生，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。- Using matlab written narrowband noise occurs, Combined with PCA scale invariant feature transform (SIFT) algorithm, BP neural network function fitting and pattern recognition.

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.