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OFDM信号的时间偏差校正程序，用于估计OFDM信号的时间偏差(OFDM signals in time warp correction procedure used to estimate the OFDM signals in time warp)

matlab经典算法，包括各种方程的例子(matlab classic algorithms, including various examples of equations)

说明：  有详细说明的手编模拟退火法及其示例，为TXT文件，复制到指定M文件即可运行(Detailed description of the hand for example, simulated annealing and for the TXT file, copy the file to run the specified M)

利用matlab将excel文件中的数据导入或导出，介绍相应函数的用法(Using matlab to excel file import or export data to introduce the usage of the corresponding function)

这是TD算法的逆过程，首先将时间序列，划分为相邻点的短序列，当然此时的拟合误差为0，因为第一点和第二点的连线，原始点都落在线段上。将相邻两个线段连接起来，此时每条线段包含三个原始点，计算中间那个点的拟合误差。这样，所有这些三个点的线段中的中间点的拟合误差计算出来后，找出误差最小且误差小于阀值R的分段，作为第一条包含三个点的线段。 在上面的基础上，第一条分段同样的和相邻线段连接，然后计算每一条分段的拟合误差，再找出误差最小且小于阀值R的分段，作为第二个分段。依次方式循环，直到所有分段的拟合误差都小于阀值R，分段结束。 (This is the reverse process of TD algorithm, the first time series is divided into short sequences adjacent dots, of course fitting error is zero at this time, because the first and second points of connection, the original point fall line on. The two adjacent segments are connected, then each segment contains three original point, the intermediate fitting error calculated that point. Thus, after all these segments fitting error of three points in the intermediate point calculated to find the minimum error and the error is less than the threshold R segment, as the first line contains three points. Based on the above, the first segment and the adjacent line segment connecting the same, and then calculate a fitting error for each segment, and then find the smallest error and less than the threshold R segment, as the second segment . Followed by a cyclic manner until all segments fitting error is less than the threshold R, segment ends.)

matlab与亚当慕斯公式结合解决运输问题！(matlab)

最优波束形成的空时过程特性（包括快拍模型、空时随即过程、阵列和孔径的谱采样等）(Optimal beamforming space-time process characteristics (including the snapshot model, then space-time process, arrays and spectral sampling of the aperture, etc.))

说明：  newmark-beta法解多个自由度的结构动力响应，并输出结构响应图形(Newmark-beta method is used to solve the structural dynamic response of two degrees of freedom and output the structural response graph.)

supervisory control in matlab for fuzzy systems

本文二次更新型粒子群算法（ TUPSO）的基本思想是：一方面，在保留粒子群算法中快速收敛， 易于实现， 调整参数少等优势的前提下，通过融合基本粒子群算法中的信息共享原理与 DPSO-TSP 中的 2-Opt 运算法则，改进了DPSO-TSP中粒子进化的规则(In this paper, the basic idea of the new particle swarm optimization (TUPSO) algorithm is: on the one hand, by integrating the particle swarm optimization algorithm in the fast convergence, easy to achieve, adjust the parameters of less advantage of the premise, through the integration of basic particle swarm algorithm information sharing Principle and the 2-Opt algorithm in DPSO-TSP improves the rule of particle evolution in DPSO-TSP)