MODASK

ex5_1 I-型线性相位FIR滤波器 ex5_2 II-型线性相位FIR滤波器 ex5_3 III-型线性相位FIR滤波器 ex5_4 IV-型线性相位FIR滤波器 ex5_5 矩形窗频响 ex5_6 希尔伯特变换器设计－汉宁窗 ex5_7 低通滤波器设计－汉明窗 ex5_8 带通滤波器设计－布莱克曼窗 ex5_9 低通滤波器设计－凯塞窗 ex5_11 频率采样技术：低通，朴素法 ex5_12 频率采样技术：低通, 最优法T1 & T2 ex5_13 频率采样技术：带通, 最优法T1 & T2 ex5_14 频率采样技术：高通, 最优法T1 ex5_15 频率采样技术：差分器 ex5_16 频率采样技术： 希尔伯特变换器 ex5_17 利用Parks-McClella算法设计低通滤波器 ex5_18 用PM算法进行的带通滤波器设计 ex5_19 用PM算法进行的高通滤波器设计 ex5_20 用PM算法进行的阶梯滤波器设计 ex5_21 用PM算法进行的差分器设计 ex5_22 用PM算法进行的希尔伯特变换器设计(ex5_1 I-type linear phase FIR filter ex5_2 II-type linear phase FIR filter ex5_3 III-type linear phase FIR filter ex5_4 IV-type linear phase FIR filter rectangular window frequency response ex5_5 Hilbert ex5_6 converter design- Hanning window low-pass filter design ex5_7- Hamming window ex5_8 bandpass filter design- Blackman window ex5_9 low-pass filter design- Kaiser window ex5_11 sampling frequency: low-pass, a simple method ex5_12 sampling frequency: low-pass, optimal method T1 & T2 sampling frequency ex5_13: band-pass, optimal method T1 & T2 ex5_14 sampling frequency: high-pass, optimal method T1 sampling frequency ex5_15: differentiator sampling frequency ex5_16: Hilbert converter Parks-McClella use ex5_17 algorithm design low-pass filter PM algorithm ex5_18 with the band-pass filter design PM algorithm ex5_19 with the high-pass filter design PM algorithm used ex5_20 ladder filter design PM algorithm used ex5_21 differential design PM al)

说明：  turbo码系统的仿真，包括编码、交织、不同译码、穿孔等各个部分的程序。仿真结果在图中表现。译码算法为log-map。(turbo code system simulation, including encoding, interleaving, different decoder, such as perforation of part of the process. Simulation results are shown in Fig. Decoding algorithm for log-map.)

一个利用感知准则进行模式分类的程序,虽然很简单,但很实用(use of a perception pattern classification criteria for the procedure, although simple, but very practical)

基于SVPWM的三电平逆变的matlab仿真，阐述了负荷预测的应用研究,车牌识别定位程序的部分功能，LCMV优化设计阵列处理信号，Matlab实现界面友好，欢迎大家下载学习，光纤陀螺输出误差的allan方差分析。( Based on SVPWM three-level inverter matlab simulation, It describes the application of load forecasting, Part of the license plate recognition locator feature, LCMV optimization design array signal processing, Matlab to achieve user-friendly, Welcome to download the study, allan FOG output error variance analysis.)

a toolbax of genetic programming in matlab

10本matlab学习的书籍，对学习matlab有很大的帮助。是很好的资料。(10 matlab learning books, learning matlab has a great help. Is a very good information.)

读入一段语音，进行基音检测，最后实现对这段语音的共振峰检测。(Read in a speech, pitch detection, and finally to achieve this period of speech resonance peak detection.)

PSO算法简单、易实现、计算量小，而且PSO 对初始点依赖性不大，具有更强的全局优化能力，也能较快的的收敛于可接受解。这是改进的pso,请多多指教。(PSO algorithm is simple, easy to realize the advantages of a small amount of computation and computational efficiency, and PSO dependence of the initial point, with stronger global optimization capability, but also faster convergence to an acceptable solution. This improved pso, exhibitions)

产生一个随机信号和两个不同频率但频率间隔很小的正弦信号，要求对两信号之和进行如下分析： （1） 求该随机信号的自相关性系数、自相关函数，画出对应的图形； （2） 利用不同的参数建模方法求出两个随机信号的功率谱； （3） 利用极大似然估计、递推最小二乘法等常用的参数估计方法估计所建模型，包括AR模型、MA模型和ARMA模型的的参数，阶次自定；并与Matlab工具箱里的一些建模函数的运算结果进行比较； （4） 利用陷波滤波和MUSIC滤波方法对该信号的频谱进行估计； （5） 利用Wiener滤波、LMS滤波对该含噪声的正弦信号进行去噪声处理； （6） 假设该信号是一个飞行器的某个方向的线位移信号，可否利用Kalman滤波对该信号进行滤波？ （7） 利用高阶谱理论对该信号进行谱估计和相应的AR模型、MA模型和ARMA模型估计； （8） 利用小波变换（变换函数可以直接用Matlab里的函数）对该信号进行去噪声处理，并和前面的去噪声方法进行比较。 (Produce a random signal and two different frequency but frequency interval small sine signals, required to make the following analysis of two signals: (1) for the random signal from the correlation coefficients, the autocorrelation function and draw the corresponding graphics (2) make use of different parameters modeling method for out two random signal power spectrum (3) using maximum likelihood estimation, recursive least square method and common parameters estimation method estimates that the model, including AR model, MA model and the parameters of the ARMA model we, order time decided oneself With Matlab toolbox and some of the modeling function is used compared the (4) use trapped wave filter and MUSIC of the signal filter method of spectrum to estimate (5) use Wiener filtering, LMS filtering on the sinusoidal signal with noise to noise treatment (6) assumes the signal is a vehicle of a certain direction of displacement signal line, can you use Kalman filtering on the)

双馈风力电机模型，可以再修改，dq坐标下模型(Doubly-fed wind-electric model can be modified, dq model coordinates)