pi_pso

Airborne LiDAR for DEM generation: some critical issues

图像灰度化处理源代码，有详尽的注释，有matlab基础的同志可以看得懂的。(Grayhound processing source code, detailed notes, matlab based comrades can understand.)

LDA学习用到的算法，不是自己写，别人的，拿来学习用(LDA learning algorithm is used, not her own writing, others, used to learn)

利用动态惩罚因子法对多学科协同优化方法进行改进，并用具体的一个算例进行了验证(Using dynamic penalty factor multidisciplinary collaborative optimization method to improve, and the specific example)

此程序能实现很好的低通滤波，能很好的滤除低频分量，对于初学图像处理的人很有用(This process can achieve a good low-pass filtering, the filter can be a very good low-frequency components, for beginners who are useful image processing)

在matlab开发环境下实现了模拟退火的智能算法程序(In the matlab development environment can only achieve a simulated annealing algorithm)

无线传感器网络定位用到的无线传输模型 Regular Model, Logarithmic Attenuation Model, DOI Model, RIM Model (Wireless sensor network localization using wireless transmission model, Regular Model, Logarithmic Attenuation Model, DOI Model, RIM Model Achieve functional distance and transmission attenuation swap ~~~~~~~~~~~~~~~~~~~~~~Regular Model~~~~~~~~~~~~~~~ In this model, the radio range is a circle ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ReceivedSignalStrength=SendingPower-PathLoss e.g, RSS=Pt-Pl(d0)-10*η*log10(dist/d0) Pt:transmit power pl(d0):the pass loss for a reference distance of d0 ηis the path loss exponent above parameters are saved in ../Parameters_Of_Models.mat dist:distance between sender and receiver(m) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ typical value:Pt=0-4dBm(max),Pl(d0)=55dB(d0=1m),η(2~4)=4(indoor,outdoor) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~Logarithmic Attenuation Model~~~~~~~~~ In this model, the radio range is a circle ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ReceivedSignal)

说明：  冈萨雷斯（matlab）书中源代码全载。(Gonzalez (matlab) the book contains all the source code.)

Matlab code to detect (invariant) Blobs in images.

在程序中用一般的MUSIC方法估计了信号的频谱，从两图中可看出在信号各频率处，频谱的峰值较大，故能明显的与噪声相区别，可在一定程度上避免在信号幅度较小时信号被噪声淹没的情况。(MUSIC method general procedures used to estimate the spectrum of the signal, it can be seen from the two graphs in the signal at each frequency of the spectrum peak larger, and it could be significantly distinguished from noise in the signal can be avoided to some extent a lesser extent, the signal is noise submerged.)