first-and-second-order-sliding-mode-controller

用来测试手机待机情况下所能使用的最大内存量，普通用函数调用得到的剩于内存是错误的，这个通过用INT占用内存来获得可以使用的内存真正空间大小(Used to test mobile phone standby cases the maximum amount of memory can be used by the general use function calls get left in the memory is wrong, it occupied by the memory by using INT can be used to obtain the real memory space)

在MATLAB里，基于dct域,实现在二维图像中嵌入数字水印 并提取。(In MATLAB, the dct-based domain, the realization of two-dimensional images in the digital watermark embedding and extraction.)

matlab实现CNN卷积神经网络，进行图像分类。(We can realize neural network with matlab, which will complete the classification of the image.)

此程序是计算wigner-ville分布、伪wigner-ville分布和平滑伪wigner-ville分布的程序，需要下载matlab时频分析工具箱(This procedure is the calculation wigner-ville distribution, pseudo-wigner-ville distribution and smooth pseudo-wigner-ville distribution procedures need to download the time-frequency analysis matlab toolbox)

说明：  二阶一领导者多智能体一致性。可用来入门学习一致性(Second order one leader multi-agent consistency. It can be used to learn consistency)

esto realmente no se que es, es una base de dartos para las señ ales ecg

Transfer Function of PID controller is given in detailed Form.And the Matlab Implementation also avialable.Help ful for Control Engineers and Technologists.

The plane stress analysis refers to the problems where the thickness of the structure is very small compared to other dimensions of the structure in the XY plane. The plane stress problem is a 2D problem. The stresses in the z direction are considered to be negligible,
 
0, the stress-strain compliance relationship for an isotropic material becomes,

基于BP和GRNN神经网络的粮食产量预测研究，通过训练样本和测试样本的交叉验证，实现粮食产量预测效果的最佳化(Prediction of Grain Yield BP and GRNN based training through cross-validation and testing samples, to achieve the best effect of the Grain Production Forecast)

基于信道的历史信息来预测不同信道的未来可用时间可以帮助CR选择一个最佳信道进行信息传递。不同的预测准则应用到周期或是随机的开关模式中。一个CR可以学习以往不同信道的模式。我们提出一个简单的分类和学习方法去检测模式的类型和收集需要的信息用于智能信道的选择。MATLAB仿真结果显示提出的方案在随机信道的随机和周期模式中都有优越的表现。随着时间的变化，新到的切换次数减少到55 ，并且延迟时间也相应减少，而吞吐量却在提高。(Prediction of future availability times of different channels based on history information helps a cognitive radio (CR) to select the best channels for control and data transmission. Different prediction rules apply to periodic and stochastic ON-OFF patterns. A CR can learn the patterns in different channels over time. We propose a simple classification and learning method to detect the pattern type and to gather the needed information for intelligent channel selection. Matlab simulations show that the proposed method outperforms opportunistic random channel selection both with stochastic and periodic channel patterns. The amount of channel switches needed over time reduces up to 55 , which reduces also the delay and increases the throughput.)