smart--antenna

Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was published by David Lowe in 1999.[1] Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, individual identification of wildlife and match moving. The algorithm is patented in the US the owner is the University of British Columbia.

creates chirp train, corresponding match filter impulse response

Breakout a game like arknoid

Program for Correlation on big data

说明：  部分遗传算法的程序，用于跟踪示例，便于比较，比较实用(Part of the genetic algorithm procedures for tracking example, ease of comparison, more practical)

对ask fsk用matlab写出 并有图像(that is a good thing)

It calculates the entropy of binary source

将喇曼光纤放大器等效成一个N信道单向波分复用系统，并且根据N信道受激喇曼散射稳态形式的解析理论给出了掺铒光纤放大器中信号光的功率的matlab仿真，此处为仿真代码。(Raman fiber amplifiers will be equivalent to an N-channel unidirectional WDM systems, and based on N-channel Stimulated Raman scattering form analytical steady-state theory gives erbium-doped fiber amplifier signal light power matlab simulation, Here for the simulation code.)

这种方法一方面将像素的灰度值分散，可以分辨图象中比较细节的内容；另一方面，将图 象的灰度变化控制在一定范围之内，抑制了噪声的产生，较大程度上地保留了原始图象的亮度．(This approach on the one hand spread the pixel gray value, the more details you can identify the contents of the image the other hand, the image gray scale control in a certain range, suppress noise generation, a greater degree preserved on the original image brightness.)

修正R-D成像算法，实现对运动点目标的正确成像！！(RD imaging algorithm is modified to realize the right of the moving point target imaging! !)