STM32 FFT算法

应用背景On the Design of ZF and MMSE Tomlinson-Harashima Precoding in Multiuser MIMO Amplify-and-Forward Relay System,it is main described the mimo system in the multi-user  scenario.the main precoding algrithm is combined the zf precoding and the MMSE precoding.关键技术we design a zero-forcing (ZF) Tomlinson-Harashima precoding (THP) and a minimum mean square error (MMSE) THP for multiuser MIMO relay system with direct link. Based on these precoding structures, we propose the optimal combining weights of the ZF THP and the MMSE THP in half duplex relay system, and the sub-optimal weights of MMSE THP to reduce feedback channel state information(CSI). Through the Monte Carlo simulation, we verify that the optimal weights combining method outperforms the constant weights combining method. In addition, we confirm that the performance of the sub-optimal weights combining method is&

This function calculates the peaks in a vector V.

c语言编的万年历源程序,可显示年份从1980-2099年,是个很实用的工具-hefty almanac series of the source, can show that the years from 1980-2099, is a very useful tool!

用标准C语言解决100道经典数学问题，堪称经典，是C程序开发员必备的C源码库，具有很强的参考价值。-using standard C language to solve 100 classical mathematical problems for his classic, C procedures required developers of C source code library, and has a strong reference value.

这个软件描述C语言用 16f877 触发一个LED，与所有配置的计时器和寄存器。

一种用matlab写的群集智能算法-蚁群算法-Of a cluster with matlab to write intelligent algorithm- ant colony algorithm

《游戏编程中的人工智能技术》书中源代码和可执行文件- Game programming in artificial intelligence technology, the book source code and executable files

几种常用的内插数值计算方法，对经常数值计算的人有帮助-several interpolation commonly used numerical calculation method, the numerical calculation of regular people to help

程序算任意点FFT和小波变换,以及可选择多种小波及小波变换后的单频带重够,另算信号的Lipschitz指数,高级数字信号处理!-counting procedures arbitrary point FFT and Wavelet Transform, and the choice of multiple wavelet and the wavelet transform of a single-band heavy enough, and another count signal Lipschitz index advanced digital signal processing!

开发的多目标优化算法采用进化优化方法和证明自己的优势在各种涉及实际问题主要是两个和三个目标，现在有一个不断增长的需求发展进化多目标优化（EMO）用于处理许多目标的算法（具有4或更多个目标）优化问题。在本文中，我们认识到一个最近几年的努力，并讨论了许多的可行方向发展潜力EMO算法求解多目标优化问题。此后，我们建议的参考点基于许多目标NSGA-II（我们称之为NSGA-III），强调人口会员，非主导且靠近一组提供的参考点。建议NSGA-III是施加到若干许多目标测试问题具有两个到15的目标，并与两个版本的一个最近比较建议EMO算法（MOEA/ D）。而每两个MOEA/ D的方法效果很好对不同类别的问题，所提出的NSGA-III被发现，以产生令人满意的结果在这项研究中考虑了所有的问题。本文介绍结果在无约束的问题，续集本文认为限制，在处理其他专科许多目标优化问题。