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
標簽： directory functions interface transform
上傳時間： 2016-08-31
上傳用戶：cooran
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]
標簽： approximate directory algorithm the
上傳時間： 2014-01-17
上傳用戶：hanli8870
A Matlab toolbox for exact linear time-invariant system identification is presented. The emphasis is on the variety of possible ways to implement the mappings from data to parameters of the data generating system. The considered system representations are input/state/output, difference equation, and left matrix fraction. KEYWORDS: subspace identification, deterministic subspace identification, balanced model reduction, approximate system identification, MPUM.
標簽： identification time-invariant presented emphasis
上傳時間： 2013-12-28
上傳用戶：wfl_yy
點對點語音通信控件V3.6，集成了G729A壓縮算法，實時傳輸協議，話音清晰流暢！使用簡單方便！適用于VC＋＋、VB、 dot NET平臺、C++Builder、Delphi、易語言及網頁應用程序等常見開發平臺。
上傳時間： 2014-11-26
上傳用戶：erkuizhang
ViedeoComm 視頻通信通信控件V3.0。VideoComm視頻通信控件，集成高性壓縮算法，實時傳輸協議，支持一對一(點對點)，一對多（廣播式）等方式的的實時視頻通信，視頻畫面清晰流暢！使用簡單方便！ VideoComm視頻通信控件適用于VC＋＋、VB、dot Net平臺、C++Builder、Delphi、易語言、網頁應用程序等各種常見的開發平臺。
標簽： ViedeoComm VideoComm 3.0 視頻通信
上傳時間： 2014-01-27
上傳用戶：lgnf
MATLAB的SVM算法實現，Matlab Support Vector Machine Toolbox，This toolbox was designed as a teaching aid, which matlab is particularly good for since source code is relatively legible and simple to modify. However, it is still reasonably fast if used with the supplied optimiser. However, if you really want to speed things up you should consider compiling the matrix composition routine for H into a mex function. Then again if you really want to speed things up you probably shouldn t be using matlab anyway... Get hold of a dedicated C program once you understand the algorithm.
上傳時間： 2013-12-20
上傳用戶：jkhjkh1982
The program constructs girth-twelve column-weight QC-LPDC codes. The rate can be changed by changing k(row-weight), size is changed by varying m(sub-matrix size).
標簽： column-weight girth-twelve constructs The
上傳時間： 2016-11-01
上傳用戶：erkuizhang
The algorith divides rows in to four equal groups. The rows are then used to from a distance graph which is then transformed into a matrix. girth of eight is maintained by avoiding six-cycles in the graph construction
標簽： rows The algorith distance
上傳時間： 2014-01-15
上傳用戶：kelimu
The "GEE! It s Simple" package illustrates Gaussian elimination with partial pivoting, which produces a factorization of P*A into the product L*U where P is a permutation matrix, and L and U are lower and upper triangular, respectively. The functions in this package are accurate, but they are far slower than their MATLAB equivalents (x=A\b, [L,U,p]=lu(A), and so on). They are presented here merely to illustrate and educate. "Real" production code should use backslash and lu, not this package.
標簽： illustrates elimination Gaussian pivoting
上傳時間： 2016-11-09
上傳用戶：wang5829
The "GEE! It s Simple" package illustrates Gaussian elimination with partial pivoting, which produces a factorization of P*A into the product L*U where P is a permutation matrix, and L and U are lower and upper triangular, respectively. The functions in this package are accurate, but they are far slower than their MATLAB equivalents (x=A\b, [L,U,p]=lu(A), and so on). They are presented here merely to illustrate and educate. "Real" production code should use backslash and lu, not this package.
標簽： illustrates elimination Gaussian pivoting
上傳時間： 2014-01-21
上傳用戶：lxm
