Convex11

Analysis of speech using LPC method

matlab 程序例子(利用matlab 求位平面)(Matlab procedures example (using Matlab for bit-plane))

k程序差分进化工具箱 - DeMatMATLAB包括拥有数百个内部函数的主包和三十几种工具包。工具包又可以分为功能性工具包和学科工具包。功能工具包用来扩充MATLAB的符号计算，可视化建模仿真，文字处理及实时控制等功能。学科工具包是专业性比较强的工具包，控制工具包，信号处理工具包，通信工具包等都属于此类。(k programs differential evolution toolbox- DeMatMATLAB including internal functions with hundreds of primary packages and several 30 kits. Kits can be divided into functional disciplines toolkit and toolkit. Function tool kit used to expand the MATLAB symbolic computation, visualization, modeling and simulation, word processing, and real-time control functions. Discipline tool kit is relatively strong professional toolkit, Control Toolkit, signal processing toolkit, communications toolkit belong to this category.)

说明：  肌电功率谱，积分肌电等；不含预处理过程。(sEMG power spectrum, integral EMG and so on; no pretreatment process.)

this are the example codes from control system engineering from NORMAN NISE

说明：  关于SAR成像的matlab程序，感觉还可以(Matlab on the SAR imaging process can feel)

绘制在收发天线间夹角不同时，天线的垂直极化三维方向图和水平极化三维方向图(Drawing the angle between the transmitting and receiving antennas is not the same, the three-dimensional antenna vertically polarized and horizontally polarized pattern dimensional pattern)

对matlab ODE的求解进行了详细的分析，并带有详细的例子（代码）可用来练习。(Matlab ODE solution on a detailed analysis, with detailed examples (code) can be used to practice.)

两种算法（LMS和RLS）实现CDMA系统盲多用户检测的仿真。结论验证了在加性高斯白招生信道下、同步DS-CDMA系统中接收机应用这两种盲多用户检测算法抑制多址干扰（MAI: multiple access interference）和码间串扰（ISI: inter symbol interference）的能力,仿真实验与理论推导相吻合。实验与理论都表明,RLS性能好于LMS，而LMS计算量明显小于RLS。(This paper discusses two algorithms (LMS and RLS) to achieve blind multiuser detection CDMA system simulation. Conclusion is verified in the Additive White Gaussian noise channel, the synchronous DS-CDMA system receiver applications both blind multiuser detection algorithm to suppress Multiple Access Interference（MAI）and Inter Symbol Interference (ISI) the ability of simulation is consistent with the theoretical. Both experiment and theory show that, RLS’s Performance is better than LMS, and the LMS ‘s computation was significantly less than RLS. )

KNN classifiers, training is training set, testing is test set, D is the distance, D=1 is mandistance D=2 is 欧氏距离 D=3是 infinite norm K is the number of selected neighbors