多层LSTM

文章介绍了某些结构优化算法，可以给初学者提供参考。(The article describes the structure of the optimization algorithm can give beginners some reference.)

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)

m=8时双极性八电平可调 信噪比 差错估计(m = 8 时 bipolar eight-level adjustable noise ratio error estimated)

非常好的关于matlab绘图的代码，可以学会绘制漂亮的二维与三维制图(Very good about matlab drawing code, you can learn to draw beautiful 2D and 3D mapping)

一篇关于实现卡尔曼滤波的新方法，运用MATLAB和Visual c实现。(An article on the new method of Kalman filter implementation, the use of MATLAB and Visual c implementation.)

快速、精确频率估计算法，噪声情况下语音信号频率估计(Fast, accurate frequency estimation algorithm, the case of speech noise frequency estimation)

C-means clustering algorithm

卡尔曼滤波应用于线性预测仿真 MATLAB仿真程序(kalman filter uesed for LP)

说明：  多无人机协同侦查、任务分配、智能决策仿真(MultiUAV cooperations control)

计算LDPC码理论性能的MATLAB程序,有例子说明,对通信系统设计很有帮助!(Calculation of theoretical performance of LDPC code MATLAB procedures have examples to illustrate the communication system design helpful!)