一个现代信号处理中谱估计例程

matlab在图像处理中的介绍详细介绍了matlab与图像有关的函数(matlab in image processing matlab introductory details and image-related functions)

Elnagar, G., et al. (1995). "The pseudospectral Legendre method for discretizing optimal control problems." IEEE Transactions on Automatic Control 40(10). 上述文章的算例2的仿真代码(Elnagar, G., et al. (1995). " The pseudospectral Legendre method for discretizing optimal control problems." IEEE Transactions on Automatic Control 40 (10). the simulation code of example 2 in the preceding article.)

这是经典的SAR成像算法，包含了RDA CSA RMA三种常见的对于点目标的成像算法(This is classic SAR imaging algorithm, including the RDA CSA RMA three common for point target imaging algorithm )

内容包括高斯混合概率假设密度滤波器仿真程序，GM-PHD滤波器提供了一种PHD滤波器工程化的方法，在无数据关联的情况下进行目标跟踪。(This algorithm is extended to accommodate mildly nonlinear target dynamics using approximation strategies from the extended and unscented Kalman filters.)

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说明：  tabu search scheduling problem using matlab

说明：  里面包含各种自适应算法，涉及多本不同的自适应书籍原文代码，可用于aec等等。(acoustic echo cancellation)

论文《As-Projective-As-Possible Image Stitching with Moving DLT》中的拼接算法，对于视差图像拼接具有一定的鲁棒性，但是对特征点数量及其分布均匀性有较高的要求。 The success of commercial image stitching tools often leads to the impression that image stitching is a “solved problem”.The reality, however, is that many tools give unconvincing results when the input photos violate fairly restrictive imaging assumptions;the main two being that the photos correspond to views that differ purely by rotation, or that the imaged scene is effectively planar.Such assumptions underpin the usage of 2D projective transforms or homographies to align photos. In the hands of the casual user,such conditions are often violated, yielding misalignment artifacts or “ghosting” in the results. Accordingly, many existing imagestitching tools depend critically on post-processing routines to conceal ghosting. In this paper, we propose a novel estimationtechnique called Moving Direct Linear Transformation (Moving DLT) that is able to tweak or fine-tune the projective warp toaccommodate the deviations of the input data from the idealized conditions. This produces as-projective-as-possible image alignmentthat significantly reduces ghosting without compromising the geometric realism of perspective image stitching. Our technique thuslessens the dependency on potentially expensive postprocessing algorithms. In addition, we describe how multipleas-projective-as-possible warps can be simultaneously refined via bundle adjustment to accurately align multiple images for largepanorama creation.

Routine to calc who succeeded in a class based on grade

microsoft synchronization sample for Oracle(Server side)