Channel

In this session, I will focus on the gridding method for fast image reconstruction from non- Cartesian data [1-5]. While gridding is not the only game in town, it is the reconstruction of choice when reconstruction time is an issue. Other reconstruction techniques include rBURS [6] and non-Cartesian iterative methods [7,8]. Non-Cartesian iterative methods generally use gridding and inverse gridding as their core operation, so even when gridding is not the right solution for an application, an understanding of gridding can be useful. I will cover the main steps of the gridding algorithm and then discuss some implementation tips that can signicantly reduce the computation time. Finally, I will present some illustrations and viewpoints that I have found to aid in an intuitive understanding of the gridding method, which can be helpful when designing the density compensation function and judging the appropriateness of gridding as a solution for a particular application.

四边形八节点等参元matlab程序，word文件，里边附带例题和源代码，并且有ANASY结果比较(Eight node isoparametric quadrilateral element matlab program)

laser analysis using matlab at various power

Reliability analysis of the original IEEE-RTS

用MATLAB实现动态聚类或迭代自组织数据分析，主要为数据分析和统计，D-S证据理论数据融合。( Using MATLAB dynamic clustering or iterative self-organizing data analysis, Mainly for data analysis and statistics, D-S evidence theory data fusion.)

Digital transmission using 16qam

无功补偿matlab/simulink仿真图，建模详细，有一定参考价值！(Reactive power compensation matlab/simulink simulation map, detailed modeling, there is a certain reference value!)

elasticsearch-river-mongodb 源码,主要讲述elasticsearch 和 mongodb 同步索引实现。可以实现自己编译。(Elasticsearch-river-mongodb source code, including elasticsearch and mongodb synchronization index. Can be compiled.)

MATLAB基础视频教程系列代码及课件 21世纪电子论坛出品(MATLAB based video tutorial series code and coursewareIn twenty-first Century produced electronic forum)

粒子群算法和基于ModelCenter求解背包问题的对比研究,包括了matlab版的粒子群算法，ModelCenter程序，以及自己的报告 (Particle swarm optimization algorithm and a comparative study based on ModelCenter knapsack problem, including the matlab version of the particle swarm algorithm, ModelCenter program, and its report)