Adaptive-Threshold

区间偏最小二乘，主要用于近红外数据处理。(Interval partial least squares, mainly for near-infrared data processing.)

messy genetic algorithm

高端的离散时间傅里叶变换计算当然是你必不可少的需要(Discrete-Time Fourier Transform Computation )

利用自然梯度算法，ML法能够很好的估计信号的信噪比,考虑雨衰 阴影 和多径影响。( Use of natural gradient algorithm, ML estimation method can be a good signal to noise ratio, Consider shadow rain attenuation and multipath effect.)

matlab7.0应用编程，中文资料，每章一个文件(Application Programming matlab7.0, English information, each devoted to a file)

由MATLAB生成的PWM的源代码，由模型搭建，输出频率50HZ，频率50HZ，芯片2812(PWM generated by the MATLAB source code, built by the model, the output frequency of 50HZ, frequency 50HZ, Chip 2812)

BP神经网络代码，使用LM算法（高斯牛顿法的改进，具有很好的鲁棒性）(BP neural network code, use the LM algorithm (modified Gauss-Newton method has good robustness))

偏振图像目标识别算法，根据四个方向的偏振信息，识别目标，内含偏振图片(Polarization image target recognition algorithm, according to the four directions of polarization information, identify targets, containing polarizing picture)

image inpainting (CS7495 Final Project Sooraj Bhat Object Removal by Exemplar-based Inpainting USING THE CODE Everything was done in Matlab and MEX (i.e. a C function callable from Matlab). First, the C code needs to be compiled. At the Matlab prompt, type: mex bestexemplarhelper.c You should then be able to run the following (which takes ~2mins on my 2GHz Pentium 4 laptop with 256MB of RAM): [i1,i2,i3,c,d,mov] = inpaint( bungee0.png , bungee1.png ,[0 255 0]) A smaller run (~25 seconds) would be: [i1,i2,i3,c,d,mov] = inpaint( bw0.png , bw2.png ,[0 255 0]) To visualize: plotall close movie(mov) SAMPLE IMAGES & RESULTS *0.png The original images ( bw and bungee ) *{1,2}.png The different fill region masks. *P2.png Plots of confidence and data terms. *P5.png Plots of original, fill region, inpainted images and confidence and data terms. Other images in the dir contain redundant information. I di)

power density estimation