matlabcx

这是一个工序调度MATLAB程序，希望对大家有用！(This is a MATLAB program scheduling process, we hope to be useful!)

基于matlab应用牛顿法解非线性方程组(the matlab Newton method for solving nonlinear equations)

关于扩展卡尔曼的matlab程序 m文件(a file of EKF about pmsm )

利用labview与matlab结合实现人脸定位算法 置入mathscript(Labview matlab combined with the use of a face localization algorithm implementation into mathscript)

Centralized CL for multi-robot system

MIMO系统的MMSE_ZF_ML算法，及其三种算法的性能比较(Performance comparison MMSE_ZF_ML algorithm MIMO system, and the three algorithms)

课程设计中首先采用Ising model的思想建立一个二维的模型，然后利用重要性抽样和Monte Carlo方法及其思想模拟铁磁-顺磁相变过程。计算了顺磁物质的能量平均值Ev、热容Cv、磁化强度M及磁化率X的值，进而研究Ev、Cv、M、X与温度T的变化关系并绘制成Ev-T图、Cv-T图、M-T图、X-T图，得出顺磁物质的内能随着温度的升高先增大而后趋于稳定值；热容Cv、磁化率X随着温度的升高先增大后减小；磁化强度M在转变温度Tc处迅速减小为零，找出铁磁相变的转变温度Tc大约为2.35(First of all, curriculum design idea of the Ising model used to establish a two-dimensional model, the importance of sampling and then use Monte Carlo simulation methods and their idea of ferromagnetic- paramagnetic phase transition process. Paramagnetic material calculated average energy Ev, heat capacity Cv, magnetization M and susceptibility X value, and then study Ev, Cv, M, X and temperature changes in the relationship between T and plotted into Ev-T map, Cv- T diagram, MT map, XT maps drawn paramagnetic material can be increased as the temperature increased and then stabilized value heat capacity Cv, magnetic susceptibility X as the temperature increases after the first minus small magnetization M in the transition temperature Tc decreases rapidly to zero Department to identify ferromagnetic phase transition around the transition temperature Tc for 2.35)

main 是主函数! 运行即可 p184是一个示意图! 另外两个文件是滤波模型(main is the main function can be run p184 is a schematic diagram! The other two files are the filter model)

说明：  matlab help 中文~~~~~~~~~~~~~~(matlab help)

As significant work was done in machine learning in past two decades, we have limited to recent articles in machine learning. A brief review of machine learning and its application can found in [Duttion and Conroy,1996). The most common supervised learning method and major implementation to various machine learning applications is artificial neural network as ANNs.