chap_8

Comparison of C++, Java, Python, Ruby and MATLAB Using Object Oriented Example _comparelanguages

说明：  对人工鱼群算法的matlab编程，二元函数优化，。。。。(Function optimization)

foeward featurrselection

book for matlab for engeniers in antena modulation..

说明：  这是一个矩阵变换器双空间矢量控制的Matlab仿真程序，有simulink和s函数，用M语言编程。是作为电力行业的研究仿真(This is a matrix converter double-space vector control, Matlab simulation program, with simulink and s functions, with the M-language programming. As a simulation of the power industry)

In this experiment you will simulate a symmetric binary communication system in which the probability that a bit is corrupted is p, that is P(receiving 0|1 sent) = P(receiving 1|0 sent) = p. To actually perform this experiment you will have to first develop a random number generator that produces binary random numbers.

Draft version of lung extraction

解相关及最小均方误差和传统多用户检测器的比较(Decorrelating and MMSE and traditional multi-user detector comparison)

说明：  matlab 程序用来计算roc曲线面积(matlab procedures used to calculate the area of roc curves)

lingjian.m-----蒙特卡罗方法 lingjian.m使用零件初始值，用蒙特卡罗方法算出总费用。其中使用了自己编制的正态分布随机数发生器产生正态分布随机数。lingjian.m是对蒙特卡罗方法的一次练习。 accyouhua为标定值的函数，而lingjian不是一个函数，在其中已给出了一组标定值的值。 退火确定标定值/unitanneal()----模拟退火 连续型多个变量组合优化问题 这是对模拟退火方法的一次练习，结果证明模拟退火确实是一个行之有效的方法。 当参数选择较好时（一般也伴随着运行时间的加长），模拟退火的结果较好，然而用MATLAB的FMIMCON()一般可达到更高的精度。(lingjian.m---- Monte Carlo method. 氀椀渀最樀椀愀渀.m Part initial value, using the Monte Carlo method to calculate the total cost. The preparation of their own normal distribution random number generator to generate normally distributed random numbers. lingjian.m is the first practice of the Monte Carlo method. accyouhua calibration value the function lingjian not a function, which gives the value of a set of calibration values. Annealing to determine the calibrated value/unitanneal ()---- Simulated Annealing 吀栀攀 continuous multiple variables combinatorial optimization problems 吀栀椀猀 is an exercise of the simulated annealing method, the results show that the simulated annealing is an effective method. 圀栀攀渀 the parameter selection is better (generally accompanied by a longer running time), simulated annealing results, however using MATLAB FMIMCON () generally achieve higher accuracy.)