TP1

用Matlab实现的音频FIR滤波，提供音频文件实例，效果很好(Implemented using Matlab audio FIR filter, to provide examples of audio files with good results)

说明：  m序列产生matlab仿真，simulink系统仿真(m sequence generator matlab simulation, Simulink system simulation)

卡尔曼滤波跟踪算法，有原有算法上进行了一定的改进(Kalman track )

（7，4）系统循环码译码器 decode_out = cyclic_decoder(decode_in) 该系统循环码译码器的生成多项式是g(x) = x^3 + x + 1 输入参数decode_in是接收到的循环码字，是1×7的行向量；输出decode_out是解 码后的信息码字，是1×4的行向量。 函数运行时，同时画出接收循环码字和译出码字的波形图。 ( (7,4) system cycle Decoder decode_out = cyclic_decoder (decode_in) cyclic code decoder of the system generating polynomial is g (x) = x ^ 3+ x+ 1 input parameters decode_in is the received codeword cycle, the row is 1 × 7 vector output decode_out solution code is the information after the code word is 1 × 4 row vector. Function to run at the same time code word and draw a circle to receive the word of the translated code waveform.)

独立分量分析用于混合信号的分离，使用的算法是快速固定点算法，3路混合信号分别为man.pcm、dragon.pcm和music.pcm(Independent component analysis for mixed-signal separation algorithm used is a fast fixed-point algorithm, 3-way mixed-signal, respectively man.pcm, dragon.pcm and music.pcm)

用此方法拟合椭圆，方法简单，运算量较小，很适合计算机变成实现。(fast ellipse fitting)

It is the corresponding testing module of the function that is specified in the training phase. test_set is a NxD matrix where N is the number of samples in the test set and D is the dimension of the feature space. true_labels is a Nx1 matrix specifying the class label of each corresponding sample s features (each row) in test_set . adaboost_model is the model that is generated by the function ADABOOST_tr .

file for hysteresis controller for bldc motor

sor消元法、共轭梯度法求解hilbert病态方程组(sor elimination method, conjugate gradient method for solving equations hilbert ill)

响应面法计算相关系数情况下结构的可靠度.已知极限状态方程，变量服从对数正态分布，变量均值和标准差已知，且知道变量的相关系数。(Response surface methodology to calculate the correlation coefficient of reliability under the circumstances structures known to limit state equation, variables lognormal distribution, the mean and the standard deviation is known variables, and that the correlation coefficient variables.)