transformer-and-small-current

PURPOSE: MCMC estimates Bayesian heteroscedastic AR(k) model imposing stability restrictions using Gibbs sampling y = b0 + y(t-1) b1 + y(t-2) b2 +,...,y(t-k) bk + E, E = N(0,sige*V), sige = gamma(nu,d0), b = N(c,T), V = diag(v1,v2,...vn), r/vi = ID chi(r)/r, r = Gamma(m,k)( PURPOSE: MCMC estimates Bayesian heteroscedastic AR(k) model imposing stability restrictions using Gibbs sampling y = b0+ y(t-1) b1+ y(t-2) b2+,...,y(t-k) bk+ E, E = N(0,sige*V), sige = gamma(nu,d0), b = N(c,T), V = diag(v1,v2,...vn), r/vi = ID chi(r)/r, r = Gamma(m,k))

【谷速软件编程】matlab源码-基于哈希编码图像检索 可以作为参考使用，程序是word版本 ([Valley] matlab source software programming speed- hash-coded image-based retri can be used as a reference, the program is a word version)

Video summarization refers to creating a summary of a video. Medical examinations like endoscopy and bronchoscopy lasts more than 20 minutes .The doctor may not have sufficient time to watch the entire video or the whole of video content may not be of interest to the examiner. Sometimes the medical video has to be sent to a specialist who is located at a distant place. In such cases, the doctor may just want to view the summary of the video instead of watching the whole video. Thus , the summary should be such that it should convey as much information about the occurrence of various incidents in the video. Video summarization plays an important role in efficient storage, quick browsing and retri of large collection of video data without losing important aspects. It also reduces transmission bandwidth efficiently when need arises. Efficient summarization of video recordings of bronchoscopic and endoscopic procedures is also highly relevant for the development of medical video libraries.

差分格式中的一种类型，matlab编程实现的，能看到明显效果。(difference format of a type, Matlab programming, and be able to see tangible results.)

费歇算法 用于模式识别等其他　工程应用方面的　问题　应用效果　良好(Fisher algorithm for pattern recognition and other aspects of engineering applications a good application effect)

Iterative Closest Point (ICP) 算法的改进型，精读高于原始版的，对点云噪声和漏洞的处理效果更好于原始版。(Iterative Closest Point (ICP) algorithm is improved, intensive than the original version.)

经典谱估计，其中包括的算法包括周期图法，平滑法BT法等经典算法~(classic spectrum estimation,including period,smooth,and BT，algorithms~)

给定虚警概率,仿真发现概率在各种干扰下的仿真曲线(Given false alarm probability, the simulation shows that the simulation curve of probability in all kinds of interference)

瑞利分布杂波幅度和高斯谱仿真，需要的可以学习看下(Rayleigh distribution clutter simulation, the need to learn a look)

machine vision calibration