RobustAdaptiveControl3

这是关于永磁同步电机的直接转矩控制的程序，而且经过验证，肯定能用。也可作为参考。(This is about the permanent magnet synchronous motor direct torque control procedures, and proven, certainly can. Can also be used as reference.)

ctpIF1005(20100416)期货数据2010年4月16日(CtpIF1005 (20100416) futures data for April 16, 2010 )

分组码是一种信道编码，本代码实现分组码的BER性能仿真,BPSK，AWGN信道的情况下。(Block code is a kind of channel coding, the code to achieve the simulation, the performance of BER codes BPSK, AWGN channel case.)

Simulink 实现的FM调制，载波13KHz，频偏3KHz，调制波形存为一个波形文件。FM解调采样双斜率鉴频，解调直接输出到声卡。(Simulink implementation of the FM modulation, carrier 13KHz, offset 3KHz, modulation waveform file saved as a waveform. FM demodulation of two-slope Kam sampling frequency, demodulated output directly to the sound card.)

曲线拟合多步预测，多个小波分解，VMD分解，神经网络集成，源代码(Curve fitting multistep prediction, multiple wavelet decomposition, VMD decomposition, neural network integration, source code)

增量式PID控制，Matlab仿真PID算法，算法原理、算法实现(Increment PID Controller)

基于经典的优化算法--模拟退火算法的旅行商问题寻优实现，该算法比较经典，可用于后续一些性能对比分析(The traveling salesman problem-- the classical optimization algorithms and simulated annealing algorithm is implemented based on the algorithm, compare the classic, can be used for the analysis of subsequent performance comparison)

利用MATLAB 提取ECG 波形数据,从图像中采集心电波形非常有用。(extracting ECG data from images)

ultrasonic image incl. correlation

说明：  CA算法可以将数量型属性划分成若干个优化的区间，它综合了分层聚类于划分聚类的优点，对于给定的不同的初始类个数，CA算法能随着迭代过程的不断进展改变类的数目，一些竞争力差的类即类的基数小于给定阙值的类将在迭代过程中不断消失，最终得到能够有效体现数据实际分布情况的优化聚类个数。(CA algorithm for quantitative attributes can be divided into a number of the interval optimization, hierarchical clustering which combines the advantages of clustering in the division, for a given number of different types of initial, CA algorithm as the iterative process the continuous progress of change in the number of categories, some categories of poor competitiveness of the base type that is less than the value of a given category Que iterative process will continue to disappear and eventually be able to effectively reflect the actual distribution of data to optimize the number of clustering.)