Matlab

自适应线性预测编码问题，利用白噪声序列生成信号序列，进而进行LMS迭代，计算滤波器权系数的轨迹曲线和衰减曲线(Adaptive linear predictive coding problem, the use of white noise sequence to generate signal sequence, and then LMS iteration to calculate the filter weights of the trajectory curve and the attenuation curve)

说明：  matlab模拟八边形光子晶体光纤，容易接受，上手快(pcf。Computing easy, fast Convenience of calculation speed. Super easy to do, accept the fast )

设计一个程序，用后向Euler 法/梯形法求解电路系统的MNA 方程（该方程由stamp 程 序得到），其中线性方程的求解采用GCR 迭代法。(Design a program that uses the backward Euler method/trapezoid method for solving circuit system MNA equation (the equation obtained by the stamp program), in which the linear equations using GCR iteration.)

OFDM系统中基于DFT的信道估计技术仿真(OFDM system channel estimation based on DFT)

多项式拟合函数，用于给定数据点的多项式拟合，区别于matlab内置的函数polyfit,但效果差别不大。(A simple way of polynomial fitting to given points ,which is different from polyfit function but with no much different in result .)

An example of an Extended Kalman Filter applied at a mechanical system.

这一程序内涵模糊控制器的FIS程序，可以做基于此做PIDmatlab仿真。(This program connotation fuzzy controller fis program, you can do based on this PID simulation.)

神经网络，基于广义同余神经网络的非线性系统辨识仿真(failed to translate)

“基于Floyd最短路算法的Ford和Fulkerson迭加算法”的最小费用最大流算法，其基本思路为：把各条弧上单位流量的费用看成某种长度，用Floyd求最短路的方法确定一条自V1至Vn的最短路；再将这条最短路作为可扩充路，用求解最大流问题的方法将其上的流量增至最大可能值；而这条最短路上的流量增加后，其上各条弧的单位流量的费用要重新确定，如此多次迭代，最终得到最小费用最大流。 (" Floyd shortest path algorithm based on the Ford and Fulkerson algorithm superposition" of the minimum cost maximum flow algorithm, the basic idea is: the flow of each arc on the unit cost as a length, with Floyd for the most short-circuit method to determine a from V1 to Vn of the most short-circuit then this can be expanded as the shortest way, by solving the maximum flow of traffic on the way to its maximum possible value and this increased the flow of the shortest path, on which the arcs of the unit to re-determine the cost of traffic, so several iterations, finally get the minimum cost maximum flow.)

jit精益生产的论文，很经典的。毕业答辩的优的哈(jit lean production of paper, very classic. Ha excellent graduate reply)