Signal-detection

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.

WSN(无线传感器网络)的初期模型建立以供后期仿真，模拟所用。(WSN (Wireless Sensor Networks) Ausgangsmodell für die Post-Simulation, die Simulation verwendet)

Kalman filter application

Function to calculate the principal curvatures on a triangular mesh. Approximations of curvature are based on local (N=1) neighborhood elements and vertices. Note: Directions of curvatures aren t calculated appropriately. Will post an updated version once this is implemented. Note that calculations at vertices with few adjacent triangles, and hence few adjacent vertices, are expanded to a greater neighborhood. Reference: 1) Chen and Schmitt (1992) Intrinsic surface properties from surface triangulation 2) Dong et al. (2005) Curvature estimation on triangular mesh, JZUS This code makes use of routines: buildInverseTriangualtion.m & removeDO.m initially written by: David Gringas. He is gratefully acknowledged

PCM编解码（Pulse-code modulation），即脉冲编码调制）(PCM codec (Pulse-code modulation), Pulse Code Modulation))

主要用于sar成像算法学习，用来生成目标回波，并用RD算法进行成像处理。(Sar imaging algorithm is mainly used for learning, used to generate the target echo imaging with RD algorithm.)

信号分析与处理，matlab语言及应用。(Signal analysis and processing, matlab language and application.)

Decompose image into subbands (undecimated wavelet), denoise, and recompose again. fh = decomp_reconst_wavelet(im,Nsc,daub_order,block,noise,parent,covariance,optim,sig) im : image Nsc: Number of scales daub_order: Order of the daubechie fucntion used (must be even). block: size of neighborhood within each undecimated subband. noise: image having the same autocorrelation as the noise (e.g., a delta, for white noise) parent: are we including the coefficient at the central location at the next coarser scale? covariance: are we considering covariance or just variance? optim: for choosing between BLS-GSM (optim = 1) and MAP-GSM (optim = 0) sig: standard deviation (scalar for uniform noise or matrix for spatially varying noise) Javier Portilla, Univ. de Granada, 3/03 Revised: 11/04

国外计算机科学经典教材 Matlab Guide to Finite Elements 《Matlab有限元分析与应用》。使用于酷爱有限元与Matlab的相关人员。(Computer Science classics teaching abroad Matlab Guide to Finite Elements Matlab finite element analysis and application. Very fond of the finite element used in the relevant personnel with Matlab.)

说明：  粒子滤波和卡尔曼的比较，希望给大家一些帮助(patical and kalman)