MATLAB-functions-reference

电源系统常用的电压控制仿真系统，研究人员必备佳品。(Power system voltage control simulation system used, the researchers required to share.)

图像配准程序，采用双线性插值，结果能运行。(Image registration process, USES the bilinear interpolation, the result can run.)

假设截获了一段短波数字通信的信号，要求解调出最终的信息，每组解调出来后，将10组信息组合起来，恢复最终的信源输出数据。 先验信息：两组数据文件，编号为1、2，每组I、Q两路存放，格式为“int16”，采样率为9600Sa/s，其中第一组为单径情况，第二组为多径情况。 参数符合MIL-STD-188-110A标准； 同步序列为syn=seq.dat，BPSK调制； 接收机频率稳定度高于1e-6。 文件中有效信息总长度为333.75s，其中同步头长为5/12s，每时隙1/6s，训练序列占10 ，在数据之前； 交织方式为全交织，矩阵交织，列为1000，在比特级进行； 纠错码码率为1/2； 调制方式为BPSK、QPSK和8PSK中的一种，映射方式为二进制，BPSK相位偏移为0，其余两种为 。 (Suppose intercepted signal for a period of short-wave digital communications requires final demodulated information after each demodulated, combining 10 group information, to restore the final output data source. Priori information: two sets of data file, numbered 1, 2, each I, Q two-way storage, the format is int16 , sampling rate 9600Sa/s, where the first group is a single path, the second group multipath situation. Parameters meet MIL-STD-188-110A standard Synchronization sequence syn = seq.dat, BPSK modulation The frequency stability of the receiver is higher than 1e-6. File payload total length of 333.75s, wherein the synchronization header length is 5/12s, each time slot 1/6s, accounting for 10 of the training sequence, before the data Interleaving for the whole interleaving matrix interleaving, as 1000, carried out at the bit level Error correction code rate of 1/2 The modulation scheme is BPSK, QPSK and 8PSK one, a binary mapping, the BPSK phase offset is 0, the )

说明：  鲁棒估计中的Huber估计，带有界面，可视化好，C#源码(Huber estimation in robust estimation, C# source code)

MATLAB软件SIMULINK工具箱的各模块功能介绍(Features of each module SIMULINK)

Greedy Group Sparsity Promoting Optmization

超结构光纤光栅基本特性，利用matlab进行仿真模拟，计算反射谱和投射普(Super-structure fiber grating basic characteristics )

统计一段文字中单词的数目，程序可运行，效果正确(The number of words in a text statistics, the program can be run, the effect is correct)

独立向量分析（IVA）是对独立成分分析（ICA）算法的一种扩展，将ICA中的单变量成分扩展为多维变量成分，可有效避免卷积盲源分离过程中的排序模糊性问题。(Independent vector analysis (IVA), a multivariate extension of independent component analysis, tackles the convolutedly mixed blind source separation (BSS) problem in a way to avoid the permutation problem by employing a multivariate source prior of the short-time Fourier transform (STFT) components. )

基于c—v模型和hough变换的圆检测，输出圆的参数(C-v model and hough transform circle detection, the output parameters of the circle)