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MATLAB has a wide variety of functions useful to the genetic algorithm practitioner and those wishing to experiment with the genetic algorithm for the first time. Given the versatility of MATLAB’s high-level language, problems can be coded in m-files in a fraction of the time that it would take to create C or Fortran programs for the same purpose. Couple this with MATLAB’s advanced data analysis, visualisation tools and special purpose application domain toolboxes and the user is presented with a uniform environmentwith which to explore the potential of genetic algorithms.

segy format sidescan analysis package

说明：  MATLAB logistic组织增长模型(MATLAB logistic)

optimization problem solve with matlab by amin zafarian

一个模拟退火matlab程序，由m文件构成的工具箱，方便大家学习。(a simulated annealing procedures Matlab, m documents constitute the toolkit to facilitate learning.)

一些关于backstepping算法的实例(some files about backstepping)

用Matlab对经过与处理后的车牌图像进行分割的程序，可以很好的把各个车牌字符都分割出来(Using Matlab with the handle of the plate after the image segmentation process can be a very good character of each plate are separate)

simulating random integer numbers

ALTERNATOR MATLAB MODEL

MATLAB30个案例配套的例子，便于学习。(Examples of MATLAB30 cases are easy to learn.)