VisibleSatellite

牛津大学 优化方法课件 optimization(oxford optimization lecture notes)

说明：  车牌识别,matlab程序的，有一个车牌，一个M文件(che pai shi bie)

FMCW体制雷达的测距测速仿真，其中包括单点目标和多点目标的探测 参考文献： [1]屈飞园,曹宁. 车载FMCW雷达准确检测多目标的一种有效方法[J]. 科学技术与工程,2012,(06):1263-1267.(FMCW system of radar ranging speed simulation, including single-point target and multi-point target detection)

在矩阵或者二维图像中画一个圆,没有丢失的像素点 (Draw a circle in a matrix/image)

有关matlab中past--power system analysis toolbox潮流计算工具箱的介绍，英文版(Matlab in the past- power system analysis toolbox toolbox flow calculation introduction, English)

图论常用算法代码，floyd，tsp的模拟退火算法等。(Used graph theory algorithm code, floyd, tsp of the simulated annealing algorithm.)

The receiver performance is quantified by depicting the receiver operating char- acteristics (ROC) curves. This curves serve as a tool to and study the performance of a sensing scheme. ROC graphs are employed to show trade-of vs between detection probability and false alarm rates, (i.e. PD versus PFA), thus allowing the determination of an optimal threshold. To illustrate the performance of energy detectors, we generate complementary ROC curves (the average probability of miss detection $ P_{md} 1 - P_d$ versus the false alarm probability $P_f$ for different receiver structures and in different fading environments.Fig. 1 illustrates the complementary ROC curves for a single channel reception (no diversity) over AWGN channels. This figure depicts the complementary ROC curves for energy detectors.

LCL filter Model m file

利用matlab求解混沌的各种类型，都有源程序，分的很细，很容易学习的(Use matlab to solve all types of chaos, there is source of very fine, very easy to learn)

该代码用于实现粒子滤波视觉目标跟踪(PF)、卡尔曼粒子滤波视觉目标跟踪(KPF)、无迹粒子滤波视觉目标跟踪(UPF)。它们是本人这两年来编写的核心代码，用于实现鲁棒的视觉目标跟踪，其鲁棒性远远超越MeanShift(均值转移)和Camshift之类。用于实现视觉目标跟踪的KPF和UPF都是本人花费精力完成，大家在网上是找不到相关代码的。这些代码虽然只做了部分代码优化，但其优化版本已经成功应用于我们研究组研发的主动视觉目标跟踪打击平台中。现在把它们奉献给大家！(These codes are used to realize particle filter based visual object tracking (PF), kalman particle filter based visual object tracking, unscented particle filter based visual object tracking. Their robustness is far beyond the classical visual object tracking algorithms such as Mean-Shift (MeanShift) and CamShift。The codes of KPF and UPF for visual object tracking cost a great of my energy, and you can not find any relating algorithm codes on internet! Our research group have optimized these codes and applied them to develop a platform for active visual object tracking. Now, I dedicate them to you and wish you love them! )