Closest Point Search in Lattices
标签： Lattices Closest Search Point
上传时间： 2017-07-02
上传用户：王者A
abel Tool Sample Requires: Visual Basic 6 and MapObjects 2.x Data: redlands.shp (Redlands sample data set from MO 2.x) Interactive Labeling Tool If the check box is checked, then the mouse down location will search for the Closest line, and label it with the street name. If the check box is not checked, then the mouse down will turn into a pan/zoom tool. There is a slider bar to control the search tolerance in screen pixels for the labeling.
标签： MapObjects Requires Redlands redlands
上传时间： 2013-12-17
上传用户：sunjet
The Hopfield model is a distributed model of an associative memory. Neurons are pixels and can take the values of -1 (off) or +1 (on). The network has stored a certain number of pixel patterns. During a retrieval phase, the network is started with some initial configuration and the network dynamics evolves towards the stored pattern which is Closest to the initial configuration.
标签： model distributed associative Hopfield
上传时间： 2015-06-17
上传用户：l254587896
ICP fit points in data to the points in model. Fit with respect to minimize the sum of square errors with the Closest model points and data points. Ordinary usage: [R, T] = icp(model,data) INPUT: model - matrix with model points, data - matrix with data points, OUTPUT: R - rotation matrix and T - translation vector accordingly so newdata = R*data + T . newdata are transformed data points to fit model see help icp for more information
标签： points the minimize respect
上传时间： 2014-01-01
上传用户：gyq
We propose a novel approach for head tracking, which combines particle filters with Isomap. The particle filter works on the low-dimensional embedding of training images. It indexes into the Isomap with its state variables to find the Closest template for each particle. The most weighted particle approximates the location of head. We develop a synthetic video sequence to test our technique. The results we get show that the tracker tracks the head which changes position, poses and lighting conditions.
标签： approach combines particle tracking
上传时间： 2016-01-02
上传用户：yy541071797
How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the Closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
标签： the decision clusters Cluster
上传时间： 2013-12-21
上传用户：gxmm
This directory includes matlab interface of the curvelet transform using usfft. Basic functions fdct_usfft.m -- forward curvelet transform afdct_usfft.m -- adjoint curvelet transform ifdct_usfft.m -- inverse curvelet transform fdct_usfft_param.m -- returns the location of each curvelet in phase-space Useful tools fdct_usfft_dispcoef.m -- returns a matrix contains all curvelet coefficients fdct_usfft_pos2idx.m -- for fixed scale and fixed direction, returns the curvelet which is Closest to a certain point on the image Demos fdct_usfft_demo_basic.m -- display the shape of a curvelet fdct_usfft_demo_recon.m -- partial reconstruction using curvelet fdct_usfft_demo_disp.m -- display all the curvelet coefficients of an image fdct_usfft_demo_denoise.m -- image denoising using curvelet
标签： directory functions interface transform
上传时间： 2016-08-31
上传用户：cooran
用prim算法实验最小生成树 本程序中用到函数adjg( )，此函数作用是通过接受输入的点数和边数，建立无向图。函数prg( )用于计算并输出无向图的邻接矩阵。函数prim( )则用PRIM算法来寻找无向图的最小生成树 定义了两个数组lowcost[max],Closest[max]，若顶点k加入U中，则令lowcost[k]=0。 定义二维数组g[ ][ ]来建立无向图的邻接矩阵。
上传时间： 2016-10-07
上传用户：tonyshao
给出一个非负小数，找出分子不超过M，分母不超过N的最简分数或整数， 使其最接近给出的小数。如果这个分数不唯一，输出‘TOO MANY’。 输入文件格式(Closest.in) 第一行，M，N（1<=M,N<=10^9） 第二行，即小数R，(0<R 输出文件格式(Closest.out) 仅一行，若解唯一输出 分子 / 分母(整数K写成K/1)，否则输出TOO MANY 样例输入： 360 120 3.1415926536 样例输出： 355/113
标签：
上传时间： 2017-01-08
上传用户：iswlkje
