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Falcon 35 MKII FM, ST/WEB, TV Digital Audio Processor

SMF-28折射率、群速度、材料色散、波导色散、总色散、包括SMF的基本底层参数。(SMF-28 refractive etc)

编写的FDTD三维的CPML 吸收边界条件总场散射场

归一化的函数，神经网络的必须。希望对大家有用。。。。(Normalized function, neural networks have. Hope to be useful. . . .)

讲述了有关matlab的函数，是很有帮助的。(Tells about the matlab function is helpful.)

文件包含matlab中常用的程序，各种算法以及应用实例的程序(File contains matlab in commonly used procedures, various algorithms and application examples of the program)

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.)

Simulation of Switched Reluctance Motor and Control Based on MATLAB Environment

信号的调制，包括BPSK,QPSK,16QAM,64QAM，(Signal modulation, including BPSK, QPSK, 16QAM, 64QAM,)

费希尔线性判别分析代码 Find the Fisher linear separator w (a column vector). X is is the training set (X is a matrix. Each row of X is a vector containing the features of a single sample). y is a column vector with the labels of the training set (1 and -1). alg is a number between 1 and 3 that specifies how to find w: alg = 1: w is the generalized eigenvalue of A,B. alg = 2: w is the solution to Bw = (mu_1-mu_2) alg = 3: solve the corresponding regression problem( Find the Fisher linear separator w (a column vector). X is is the training set (X is a matrix. Each row of X is a vector containing the features of a single sample). y is a column vector with the labels of the training set (1 and-1). alg is a number between 1 and 3 that specifies how to find w: alg = 1: w is the generalized eigenvalue of A,B. alg = 2: w is the solution to Bw = (mu_1-mu_2) alg = 3: solve the corresponding regression problem)