@fotf

说明：  induction motor simulation using s-function.real tim/e

load flow analysis using newton raphson method

这个可以用在元胞自动机仿真车流里增加新车进入(add it)

数据互联算法。绘制出了目标真是轨迹、测量轨迹、PDAF估计轨迹和NNSF估计轨迹，并进行了对比分析。(Data Association Algorithm. Drawn out of the goal really track the trajectory measurements, PDAF estimated trajectory and NNSF estimated trajectory, and a comparative analysis.)

说明：  多径传输的源程序 matlab程序示例(multipath transmission of the source Matlab procedures example)

自编的快速傅里叶变换的matlab程序，已经经过调试了，是可用的(Self matlab program fast Fourier transform, has been debugged, it is available)

Ctrl2cap Keyboard Filter Example keyboard filter driver for NT4 and Win2K

此程序是柔顺机构的拓扑优化，以柔度最小为目标函数，以体积分数为约束条件(matlab code for compliant mechanism )

说明：  一种改进的局部线性嵌入算法，性能比传统的要好(An improved local linear embedding algorithm with better performance than the traditional LLE algorithm)

给定观测序列 O=O1O2O3…Ot和模型参数λ=(A,B,π)，怎样有效计算某一观测序列的概率，进而可对该HMM做出相关评估。例如，已有一些模型参数各异的HMM，给定观测序列O=O1O2O3…Ot，我们想知道哪个HMM模型最可能生成该观测序列。通常我们利用forward算法分别计算每个HMM产生给定观测序列O的概率，然后从中选出最优的HMM模型。(Given the observation sequence O = O1O2O3 ... Ot and model parameters λ = (A, B, π), how to effectively calculate the probability that a single observation sequence, and thus can make the relevant assessment of the HMM. For example, there are a number of different model parameters HMM, given the observation sequence O = O1O2O3 ... Ot, we want to know which model is most likely to generate the HMM observation sequence. Usually we use forward algorithm calculates the probability of a given observation sequence O generated for each HMM, HMM and then to choose the best model.)