hw2_ar

模拟两个相干的的窄带信号。阵列的阵元数为10，快拍数为200，信号入射方向分别为20°，60°，阵元间距为入射信号波长的1／2，信噪比为20dB。分别用MUSIC算法和改进MUSIC算法进行仿真。仿真结果如下图所示(MUSIC algorithm is improved compared with the simulation of signal coherent MUSIC algorithm. Two coherent analog narrowband signal. Array element number of the array 10, the number of snapshots 200, a signal incident directions, respectively 20 °, 60 °, array element spacing is 1/2 of the wavelength of the incident signal, SNR is 20dB. Respectively MUSIC MUSIC algorithm and improved algorithm simulation.)

算术编码的matlab实现 ，便于无损压缩 (Arithmetic coding matlab implementation, ease of lossless compression)

电力仿真软件PSCAD直流转化器模型，很好的参考资料(Power simulation software PSCAD DC converter model, a good reference)

关于最小频移键控的五篇很好的文章：GMSK调制信号的仿真.caj，MSK数字化调制解调技术研究.nh，最小频移键控系统实现技术的仿真研究(1).caj，最小频移键控系统实现技术的仿真研究.caj，最小移频健控信号的特点分析.caj(Minimum Shift Keying on the five good article: GMSK modulation signal simulation. Caj, MSK modulation and demodulation of digital technology research. Nh, Minimum Shift Keying System Simulation Technology (1). Caj, the smallest Frequency Shift Keying System Simulation Technology. caj, the smallest frequency shift Keying signal characteristics analysis. caj)

遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法，它最初由美国Michigan大学J.Holland教授于1975年首先提出来的(Genetic Algorithm (based Algorithm) is a simulation Darwin the evolution natural selection and Genetic mechanism of biological evolution process calculation model, is a kind of searching optimal solution by simulating the natural evolution process of the method, it initially by the university of Michigan J.H olland first proposed in 1975, professor)

* Oxidization of Ammonia to Nitric Oxide *

OQPSK信号matlab/simulink仿真程序，(OQPSK signal matlab/simulink simulation program)

PROGRAMATION PAR MATLAB POUR RESOUDRE DES EQUATION

电力系统稳定器，maylab模型，有无pss。功能测试良好。(pss，matlab model,it can work welll. )

改代码使用CCE方法来实现数据挖掘中多示例学习的过程。(CCE implements the algorithm described in [1], where Gaussian kernel LibSVM [2] is used as the base learner for transformed feature vectors.)