homework2

gmsk调制信号的产生，包括求解相位、正余弦表的量化、眼图的产生以及相位路径图的产生(gmsk modulated signal generation, including the solving phase, sine and cosine tables to quantify eye map generation and the generation of phase)

处理混合整数规划问题,可以方便计算整数规划问题(Handle mixed integer programming problem)

说明：  使用人工势场法APF完成机器人的避障及路径规划(Using APF to complete obstacle avoidance and path planning of robot)

说明：  用MATLAB编写的svm源程序，可以实现支持向量机。(Prepared using MATLAB source SVM, support vector machine can be achieved.)

柯斯达斯实现载波恢复costas m-file (costas m-file costas m-file )

对周期排布的介质柱上钻有小孔的结果进行平面波的分析(cycle arrangement of the media column of drilling a small hole results plane wave analysis)

对任意给定的n顶点的复杂网络的最大似然函数法链路预测（分层随机图）(Any given n vertices complex network maximum likelihood function method link prediction (stratified random map))

感应双馈发电机系统的仿真，有借鉴意义哦，基于混沌的模拟退火算法。( Simulation of doubly fed induction generator system, There are reference Oh, Chaos-based simulated annealing algorithm.)

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)

说明：  LVQ(Learning Vector Quantization ) lvq vector quantization algorithm for the simulation program matlab.