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  • % EM algorithm for k multidimensional Gaussian mixture estimation % % Inputs: % X(n,d) - input da

    % EM algorithm for k multidimensional Gaussian mixture estimation % % Inputs: % X(n,d) - input data, n=number of observations, d=dimension of variable % k - maximum number of Gaussian components allowed % ltol - percentage of the log likelihood difference between 2 iterations ([] for none) % maxiter - maximum number of iteration allowed ([] for none) % pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) % Init - structure of Initial W, M, V: Init.W, Init.M, Init.V ([] for none) % % Ouputs: % W(1,k) - estimated weights of GM % M(d,k) - estimated mean vectors of GM % V(d,d,k) - estimated covariance matrices of GM % L - log likelihood of estimates %

    標(biāo)簽: multidimensional estimation algorithm Gaussian

    上傳時(shí)間: 2013-12-03

    上傳用戶:我們的船長(zhǎng)

  • Oracle調(diào)用接口

    Oracle調(diào)用接口, Initial makefiles created for following compilers: * Borland 5.5 Compiler and command-line tools * MinGW

    標(biāo)簽: Oracle 接口

    上傳時(shí)間: 2014-08-13

    上傳用戶:weiwolkt

  • Oracle調(diào)用接口

    Oracle調(diào)用接口, Initial makefiles created for following compilers: * Borland 5.5 Compiler and command-line tools * MinGW

    標(biāo)簽: Oracle 接口

    上傳時(shí)間: 2014-01-02

    上傳用戶:頂?shù)弥?/p>

  • 科信客戶關(guān)系管理系統(tǒng)源碼 這個(gè)是我第一次有VS2003+Mssql做的一個(gè)簡(jiǎn)單客戶管理系統(tǒng) 主要功能有: 錄入客戶 我的意向 我的保護(hù) 我的合同 工作日志 公司搜索 添加用戶 意

    科信客戶關(guān)系管理系統(tǒng)源碼 這個(gè)是我第一次有VS2003+Mssql做的一個(gè)簡(jiǎn)單客戶管理系統(tǒng) 主要功能有: 錄入客戶 我的意向 我的保護(hù) 我的合同 工作日志 公司搜索 添加用戶 意向客戶 保護(hù)客戶 合同管理 用戶管理 日志管理 DB_51aspx下為數(shù)據(jù)庫文件,附加后請(qǐng)修改data.cs中的Sql連接字符串并編譯(默認(rèn):Data Source=(local) Initial Catalog=CRMS User ID=sa Pwd=sa) 默認(rèn)管理帳號(hào)/密碼:admin/51aspx,測(cè)試帳號(hào)/密碼:test/51aspx 密碼采用SHA1加密 注意:該項(xiàng)目為VS2003轉(zhuǎn)換到VS2005

    標(biāo)簽: Mssql 2003 管理系統(tǒng) VS

    上傳時(shí)間: 2014-07-24

    上傳用戶:libenshu01

  • this directory contains the following: * The acdc algorithm for finding the approximate general

    this directory contains the following: * The acdc algorithm for finding the approximate general (non-orthogonal) joint diagonalizer (in the direct Least Squares sense) of a set of Hermitian matrices. [acdc.m] * The acdc algorithm for finding the same for a set of Symmetric matrices. [acdc_sym.m](note that for real-valued matrices the Hermitian and Symmetric cases are similar however, in such cases the Hermitian version [acdc.m], rather than the Symmetric version[acdc_sym] is preferable. * A function that finds an Initial guess for acdc by applying hard-whitening followed by Cardoso s orthogonal joint diagonalizer. Note that acdc may also be called without an Initial guess, in which case the Initial guess is set by default to the identity matrix. The m-file includes the joint_diag function (by Cardoso) for performing the orthogonal part. [init4acdc.m]

    標(biāo)簽: approximate directory algorithm the

    上傳時(shí)間: 2014-01-17

    上傳用戶:hanli8870

  • Because of the poor observability of Inertial Navigation System on stationary base, the estimation

    Because of the poor observability of Inertial Navigation System on stationary base, the estimation error of the azimuth will converge very slowly in Initial alignment by means of Kalmari filtering, and making the time Initial alignment is longer. In this paper, a fast estimation method of the azimuth error is creatively proposed for the Initial alignment of INS on stationary base. On the basis of the the fast convergence of the leveling error, the azimuth error can be directly calculated. By means of this fast Initial alignment method, the time of Initial alignment is reduced greatly. The computer simulation results illustrate the efficiency of the method.

    標(biāo)簽: observability Navigation estimation stationary

    上傳時(shí)間: 2014-01-03

    上傳用戶:wuyuying

  • The "1818" is my first search word in this website, So I upload Lcd drive(Ssd1818a) C language code

    The "1818" is my first search word in this website, So I upload Lcd drive(Ssd1818a) C language code as my support. 96*64 dot matrix Graphic LCD controller: SSD1818A Parallel interface Initial routine code Command write and Data write Base functions and application code Ascii font library Product Photo Mcu: Pic16F887...etc. Keywords: Ssd1818a, dot matrix graphic, Parallel interface, Initial routine, base font8x8 librarys

    標(biāo)簽: 1818 language website search

    上傳時(shí)間: 2016-11-05

    上傳用戶:趙云興

  • December 19, 2006 - Ant 1.7.0 Available Apache Ant 1.7.0 is now available for download. Ant 1.7

    December 19, 2006 - Ant 1.7.0 Available Apache Ant 1.7.0 is now available for download. Ant 1.7 introduces a resource framework. Some of the core ant tasks such as <copy/> are now able to process not only file system resources but also zip entries, tar entries, paths, ... Resource collections group resources, and can be further combined with operators such as union and intersection. This can be extended by custom resources and custom tasks using resources. Ant 1.7 starts outsourcing of optional tasks to Antlibs. The .NET antlib in preparation will replace the .NET optional tasks which ship in Ant. Support for the version control system Subversion will be only provided as an antlib to be released shortly. Ant 1.7 fixes also a large number of bugs. Ant 1.7 has some Initial support for Java6 features.

    標(biāo)簽: Ant Available available December

    上傳時(shí)間: 2014-01-06

    上傳用戶:daoxiang126

  • function [U,V,num_it]=fcm(U0,X) % MATLAB (Version 4.1) Source Code (Routine fcm was written by R

    function [U,V,num_it]=fcm(U0,X) % MATLAB (Version 4.1) Source Code (Routine fcm was written by Richard J. % Hathaway on June 21, 1994.) The fuzzification constant % m = 2, and the stopping criterion for successive partitions is epsilon =??????. %*******Modified 9/15/04 to have epsilon = 0.00001 and fix univariate bug******** % Purpose:The function fcm attempts to find a useful clustering of the % objects represented by the object data in X using the Initial partition in U0.

    標(biāo)簽: fcm function Version Routine

    上傳時(shí)間: 2014-11-30

    上傳用戶:二驅(qū)蚊器

  • Batch version of the back-propagation algorithm. % Given a set of corresponding input-output pairs

    Batch version of the back-propagation algorithm. % Given a set of corresponding input-output pairs and an Initial network % [W1,W2,critvec,iter]=batbp(NetDef,W1,W2,PHI,Y,trparms) trains the % network with backpropagation. % % The activation functions must be either linear or tanh. The network % architecture is defined by the matrix NetDef consisting of two % rows. The first row specifies the hidden layer while the second % specifies the output layer. %

    標(biāo)簽: back-propagation corresponding input-output algorithm

    上傳時(shí)間: 2016-12-27

    上傳用戶:exxxds

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