semiparameter_sin_eg

说明：  基于最小方差法低通FIR的设计说明书,单通带,有详细的步骤及相关理论知识(Minimum variance method low-pass FIR-based design specification, a single passband, with detailed steps and theoretical knowledge)

采用谱减法的语音降噪实现代码，适用于语音和音频系统中，可直接调用。(Speech noise reduction using spectral subtraction implementation code, for voice and audio systems, can be called directly.)

利用matlab平台，使用蒙特卡洛的方法模拟赌徒问题(Using matlab platform, the use of Monte Carlo simulation problem gamblers)

electric motor with torque speed control

远场波束形成，MVDR波束形成，最小方差无失真响应(Far-field beamforming, MVDR beamforming, minimum variance distortion response)

说明：   有一个长度为整数L(1<=L<=10000)的马路，可以想象成数轴上长度为L的一个线段，起点是坐标原点，在每个整数坐标点有一棵树，即在0,1,2，...，L共L+1个位置上有L+1棵树。 现在要移走一些树，移走的树的区间用一对数字表示，如 100 200表示移走从100到200之间（包括端点）所有的树。 可能有M(1<=M<=100)个区间，区间之间可能有重叠。现在要求移走所有区间的树之后剩下的树的个数。 输入： 两个整数L(1<=L<=10000)和M(1<=M<=100)。 接下来有M组整数，每组有一对数字。 输出： 可能有多组输入数据，对于每组输入数据，输出一个数，表示移走所有区间的树之后剩下的树的个数。(Has a length of integer L (1 &lt = L &lt = 10000) of the road, one can imagine a number line segment of length L, the starting point is the coordinate origin, each integer coordinate points in a tree, i.e. 0,1 , 2, ..., L total has L+1 L+1 positions on the tree. Now to remove some trees, tree removed by a range of digitally represented, such as 100 200 represents removed (inclusive) between 100 and 200 all the trees. There may be M (1 &lt = M &lt = 100) intervals, there may be overlap between the intervals. Now, after the number of trees require the removal of all remaining sections of the tree. Input: two integer L (1 &lt = L &lt = 10000) and M (1 &lt = M &lt = 100). Then there is an integer M groups, each with a pair of numbers. Output: there may be multiple sets of input data, for each set of input data, the output of a number indicating the number of the removal of all remaining sections of the tree after tree.)

这是一个基本的PCA方法实现人脸图像压缩与重建，可以非常快捷的将一些无法辨别的人脸图像进行快速的拼接。(This is a basic PCA method to achieve image compression and reconstruction of the face, can be very quick to identify the human face that can not be quickly spliced images.)

说明：  基于双耦合Duffing振子的随机相位正弦信号检测 采用双耦合混沌振子阵列实现了随机相位微弱正弦信号的检测，在此基础上，提出了新的检测方法，即利用单个耦合混沌振子，通过临界及周期状态 的变化检测随机相位微弱正弦信号并大致估计信号相位范围，该方法比双耦合混沌振子阵列法简单，更易于实现。(Based on double coupled Duffing oscillators random phase sine signals detected by two coupled chaotic oscillator arrays to achieve a random phase weak sinusoidal signal detection, in this basis, the proposed new detection methods, namely the use of a single coupled chaotic oscillators, through the critical and the cycle random phase state change detection and generally weak sinusoid signal phase estimated the scope of the method than the two-coupled chaotic oscillators array method is simple and more easy to implement.)

Calc standard error of the mean or non-parametric confidence intervals for samples of a time series

Artificial Intellegence: backpropagation