PuSu

mpedance matrix by the method

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.)

When you use the Microsoft Automation functions VariantTimeToSystemTime to convert variant time to system time and the SystemTimeToVariantTime to convert system time to variant time, the milliseconds value appears as zero or is ignored

Quadrature filters point detector in scale-space

QAM载波跟踪程序，用matlab写的，小程序，很实用，可以看看(QAM carrier recovery)

信号的仿真，误码率的仿真，互相学习，互相进步(change zhe singal，and find the rate of error)

Matlab function for image proecssing

simulation bad three level

solving the wave equation

主动噪声控制的经典FX-lms算法仿真，包括算法框图，结果分析(Active Noise Control of the classic FX-lms algorithm)