analyze-nonstationary-time-

a program to simulate the position of the sun in the sky by two angles the altitude and the azimuth

比较不同信道下的OFDM符号同步的算法，包括高斯，多径信道等。(Comparison under different channel OFDM symbol synchronization algorithms, including Gaussian, such as multi-path channel.)

CC2530的定时器实验，使用IAR编写。(CC2530 key experiments, using IAR preparation procedures.)

说明：  matlab代码 适用于鲸鱼寻优算法，初级教程(Matlab code for whale optimization algorithm, primary tutorial)

现代通信系统(matlab版本)第二版，第一章的第二个例题程序.(Modern communication systems (matlab version) second edition, the first chapter of the second Example program.)

esay to use but long program if want to play around with

加你如何快速的熟悉和掌握matlab语言，以及在矩阵运算和数据分析方面的应用(Plus you how to quickly become familiar with and master the matlab language, as well as matrix operations and data analysis applications)

The Techniques and an Efficient PAPR Reduced Method of OFDM Systems(The Techniques and an Efficient PAPR Reduc ed Method of OFDM Systems)

Converts binary data of any format in a string to floating point decimals of a defined fraction size. the intsize input parameter defines the size of the exponent and sets the fixed point location in the binary number. se accompanied matlab program for test of this function

摘　要:提出一种新的基于Pareto多目标进化免疫算法(PMEIA)。算法在每一代进化群体中选取最优非支配抗体保存到记忆细胞文档中 同时引入Parzen窗估计法计算记忆细胞的熵值,根据熵值对记忆细胞文档进行动更新,使算法向着理想Pareto最优边界搜索。此外,算法基于点在目标空间分况进行克隆选择,有利于得到分布较广的Pareto最优边界,且加快了收敛速度。与已有算法相比, PMEIA在收敛性、多样性,以及解的分布性方面都得到很好的提高。(Abstract:This paperproposed a new pareto-based multi-object evolutionary mi mune algorithm(PMEIA). PMEIA selected optmi alnon-dominated antibodieswhichwere then reserved inmemory cellarchive, and introducedParzenwindow to calculate entropy ofmemory cells. Updated thememory cell archive according to entropy ofmemory cells. This guarantees the conver- gence to the true Pareto fron.t Moreover, the performance of clone selection was dependent on distribution in the objective space, whichwas favorable forgetting awidely spreadPareto frontand mi proving convergence speed. Comparedwith the exis- ted algorithms, the obtained solutions ofPMEIA havemuch betterperformance in the convergence, diversity and distribution.)