一个数据深度挖掘算法matlab开发程序

matlab 与ENVI中数据格式转换，可以很好地实现两者之间的数据格式转换，包括enviwrite,enviread等(matlab with ENVI data format conversion, you can achieve a good conversion between data formats, including enviwrite, enviread etc.)

用粒子群算法求解单一水库优化调度，只需要修改相应的约束条件就可以进行优化计算了(With a single particle swarm algorithm is optimizing reservoir operation, only need to modify the corresponding constraint conditions can were optimized )

说明：  music算法','capon算法','bartlett算法',对比(MUSIC algorithm ','capon algorithm','bartlett algorithm ', comparison)

STFT与WT的缺点比较明显，随着现代信号处理技术的发展，STFT与WT已经越来越不能够满足现阶段的信号处理需求，主要是很多情况下，它俩提取的信号特征太糙，不够清晰。这也导致了很多用于提高“时频分辨率”的新技术的产生，而“同步压缩小波”（SST）就是产生于这样的背景。

北京理工大学王菲教授讲述的大学物理及力学和热学的内容(Beijing Institute of Technology Professor Wang Fei told a university physics and mechanical and thermal content of)

卷积的意义和合成地震记录的制作Convolution meaning and synthetic seismic recording production(Convolution meaning and synthetic seismic recording production)

DESIGN OF A NEURAL PREDICTIVE CONTROLLER FOR NONHOLONOMIC MOBILE ROBOT BASED ON POSTURE IDENTIFIER

Digital filter implementation examples

c++ 通用弹道仿真计算程序(经典版) 程序源代码(c++ common trajectory simulation program (classic version) source code)

猴群算法（MA）是由Zhao和Tang提出的一种新的用于求解大规模、多峰优化问题的智能优化算法.其思想在于通过模拟自然界中猴群爬山过程中爬、望和跳的几个动作，设计了三个搜索过程：爬过程主要用来搜索当前所在位置的局部最优解；望过程主要通过眺望来搜索邻近领域比当前位置更优的解，以便加速最优解的搜寻过程；跳过程的目的在于由当前搜索区域转移到其它区域,以避免搜索过程陷入局部最优(Monkey swarm algorithm (MA) is a new intelligent optimization algorithm proposed by Zhao and Tang for solving large-scale and multi-peak optimization problems. Its idea is to design three search processes by simulating several movements of climbing, looking and jumping of monkeys in nature. The climbing process is mainly used to search the local part of the current location. Optimal solution; Looking process mainly searches for solutions in adjacent areas that are better than the current location by looking over, so as to speed up the search process of the optimal solution; The purpose of jumping process is to shift from the current search area to other areas, so as to avoid the search process falling into local optimum.)