acquire

In this paper, we investigate the timing and carrier frequency offset (CFO) synchronization problem in decode and forward cooperative systems operating over frequency selective channels. A training sequence which consists of one orthogonal frequency-division multiplexing (OFDM) block having a tile structure in the frequency domain is proposed to perform synchronization. Timing offsets are estimated using correlation-type algorithms. By inserting some null subcarriers in the proposed tile structure, we propose a computationally efficient subspace decomposition- based algorithm for CFO estimation. The issue of optimal tile length is studied both theoretically and through simulations. By judiciously designing the tile size of the pilot, the proposed algorithms are shown to have better performance, in terms of synchronization errors and bit error rate, than the time-division multiplexing-based training method and the computationally demanding space-alternating generalized expectation-maximization

crossover and mutaion for binary genetic algorithm

this is create template using matlab

matlab中的贝叶斯网络工具箱，版本为1.0.4。(Bayesian network toolbox in matlab, version 1.0.4.)

说明：  S变换的源代码，实现对各种信号的频谱分析。该方法优越于短时傅里叶变换。(S transform source code, and the analysis of the spectrum of various signals. This method is superior to the short time Fourier transform.)

聚类重要步骤，利用数据之间的相似度自适应确定类别数(decide adaptive number of classes using similarity)

用于轴的校核。之前做课程设计的时候自己写的，根据《机械设计课程设计》王军 田同海 何晓玲著这本书上的公式编写。(According to the formula design of mechanical design, Wang Juntian and Hai He Xiaoling wrote the formula in this book.)

画出直方图，并将该直方图均衡化，以达到图像画面均匀。(Draw the histogram and the histogram equalization in order to achieve uniformity of the image screen.)

说明：  主成分分析算法，有大量数据，初学者可以根据数据看程序，并且可以出现图像(Principal component analysis algorithm, there is a large amount of data, beginners can look at program according to the data, and can appear the image)

无循环实现S变换，S变换在信号分析中十分有效，它的时空分辨率要高于小波变换，效率很高的程序(This code computes the Stockwell transform (S-Transform) of a one dimensional series without for loop, thereby making it computationally fast and simple. S-Transform was proposed in 1996. A nice tutorial on S-Transform can be found here: djj.ee.ntu.edu.tw/S_Transform.pdf‎ )