entropy

支持向量机SVM的应用介绍 支持向量机SVM的应用介绍(Application of support vector machine SVM support vector machine introduction to the application of SVM)

将NSGA-II 的理念融入粒子群中，并加入保存优秀解的机制，提出MPSO算法。针对MPSO 易陷入局部极值的缺点，加入变邻域机制，通过随机的破坏旧解和重建新解，找到全局最优解，以达到帮助粒子跳出局部极值的目的，提 出VNS-MPSO 算法。(Will the NSGA- II concept into particle swarm, and join save good solution mechanism, MPSO algorithm is put forward. Against disadvantages of MPSO easy to fall into local extremum, join the variable neighborhood mechanism, through the random destruction of the old and rebuild the new solution, find the global optimal solution, to achieve the purpose of help particles jump out of local extremum, The VNS- MPSO algorithm.)

This source code use neural object to help student to understand the way to design the neural network using perceptron rule.

说明：  利用速率方程的方法，对VCSOA放大器的增益特性进行模拟仿真，(Using rate equation method, VCSOA amplifier gain characteristics of simulation)

文件包含现代信号处理的常用算法的matlab源代码(File contains commonly used algorithm modern signal processing matlab source code)

分析蔡氏电路的相轨迹图,画出了各个变量的三维、二维相图 (Chua' s circuit analysis phase trajectory diagram depicts the various variables dimensional, two-dimensional phase diagram)

FEM2D_STOKES_SPARSE_BIG_CAVITY is a square region that is 1 unit wide and 1 unit high. The tangential velocity is specified to be 1 along the top boundary, with a zero normal component. On all other parts of the boundary, the velocity is specified to be zero.

matlab C++混编程序，用C++处理数据，由matlab显示画图(matlab C++ mixed program, with C++ process the data displayed by the matlab drawing)

这是研究生毕业论文做的项目——基于粒子滤波和卡尔曼滤波的卫星定位技术。附件中包含了无线信道估计和均衡、TDOA测距、IMM-KF滤波的所有程序，希望对从事无线定位技术的开发人员有帮助。独家奉献。(This is the project graduate thesis do-- Based on satellite positioning technique of particle filter and Calman filter. Annex contains all the applications of wireless channel estimation and equalization, TDOA distance, IMM-KF filter, and they hope to help in the wireless location technology development personnel. Exclusive dedication.)

Survival times are data that measure follow-up time from a defined starting point to the occurrence of a given event, for example the time from the beginning to the end of a remission period or the time from the diagnosis of a disease to death. Standard statistical techniques cannot usually be applied because the underlying distribution is rarely Normal and the data are often ‘censored’. A survival time is described as censored when there is a follow-up time but the event has not yet occurred or is not known to have occurred. For example, if remission time is being studied and the patient is still in remission at the end of the study, then that patient’s remission time would be censored. If a patient for some reason drops out of a study before the end of the study period, then that patient’s follow-up time would also be considered to be