Simulation_code_DSB_SC

the code i have uploaded estimate the position of speaker,in environment put a number of microphones that by extended kalman filter estimate the position of speaker

Gauss_Seidel迭代法的Matlab程序 (Gauss_Seidel iteration of the Matlab program)

M-files for sample fir and iir filter design

计算瑞雷波频散曲线GUI小程序，matlab写，内含使用说明(Rayleigh wave dispersion curves calculated GUI applet, matlab write, containing instructions for use)

说明：   有一个长度为整数L(1<=L<=10000)的马路，可以想象成数轴上长度为L的一个线段，起点是坐标原点，在每个整数坐标点有一棵树，即在0,1,2，...，L共L+1个位置上有L+1棵树。 现在要移走一些树，移走的树的区间用一对数字表示，如 100 200表示移走从100到200之间（包括端点）所有的树。 可能有M(1<=M<=100)个区间，区间之间可能有重叠。现在要求移走所有区间的树之后剩下的树的个数。 输入： 两个整数L(1<=L<=10000)和M(1<=M<=100)。 接下来有M组整数，每组有一对数字。 输出： 可能有多组输入数据，对于每组输入数据，输出一个数，表示移走所有区间的树之后剩下的树的个数。(Has a length of integer L (1 &lt = L &lt = 10000) of the road, one can imagine a number line segment of length L, the starting point is the coordinate origin, each integer coordinate points in a tree, i.e. 0,1 , 2, ..., L total has L+1 L+1 positions on the tree. Now to remove some trees, tree removed by a range of digitally represented, such as 100 200 represents removed (inclusive) between 100 and 200 all the trees. There may be M (1 &lt = M &lt = 100) intervals, there may be overlap between the intervals. Now, after the number of trees require the removal of all remaining sections of the tree. Input: two integer L (1 &lt = L &lt = 10000) and M (1 &lt = M &lt = 100). Then there is an integer M groups, each with a pair of numbers. Output: there may be multiple sets of input data, for each set of input data, the output of a number indicating the number of the removal of all remaining sections of the tree after tree.)

粒子滤波算法预测电池寿命。包括电池容量数据和MATLAB程序。(The RUL prediction of battery based on partical filter. Including battery capacity data and matlab code.)

数值分析的实验，拉格朗日、分段线性、三次样条等(Analysis of the experiment, Lagrangian, piecewise linear, cubic spline, etc.)

少数博弈，实现少数者博弈模型，没有优化，只是粗略的实现其功能。。(ying wen miao shu jiu suan le！)

针对传统α － β 滤波算法不够有效跟踪机动目标的问题， 详细分析了其内在原因， 提出一种改进的α － β 滤波算法。该算法不需要假定目标的机动模型， 而是将目标的机动加速度作为滤波状态直接估计出来， 将估计加速度作为输入控制量引入到传统α － β 滤波器的状态估计方程中进行机动目标的跟踪。然后将它与传统α － β 滤波算法进行比较， 证明了新的算法不仅具有传统算法计算量小的优点， 而且还可以对机动目标进行实时跟踪。仿真结果表明， 新算法在综合性能上明显优于传统算法。(In view of the problem that the traditional alpha beta filtering algorithm is not effective in tracking the maneuvering target, the internal reason is analyzed in detail, and an improved alpha beta filtering algorithm is proposed. In this algorithm, the maneuvering model of the target is not assumed, but the maneuvering acceleration of the target is estimated directly as the filter state, and the estimated acceleration is introduced into the state estimation equation of the traditional alpha beta filter to track the maneuvering target in the state estimation equation of the traditional alpha beta filter. Then compared with the traditional alpha beta filtering algorithm, it is proved that the new algorithm not only has the advantages of small computation in the traditional algorithm, but also can track the maneuvering target in real time. The simulation results show that the new algorithm is superior to the traditional algorithm in terms of comprehensive performance.)

matlab对图形处理车牌倾斜校正实现的仿真实现等等(matlab correct license plate)