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
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]
标签： approximate directory algorithm the
上传时间： 2014-01-17
上传用户：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.
标签： identification time-invariant presented emphasis
上传时间： 2013-12-28
上传用户：wfl_yy
点对点语音通信控件V3.6，集成了G729A压缩算法，实时传输协议，话音清晰流畅！使用简单方便！适用于VC＋＋、VB、 dot NET平台、C++Builder、Delphi、易语言及网页应用程序等常见开发平台。
上传时间： 2014-11-26
上传用户：erkuizhang
ViedeoComm 视频通信通信控件V3.0。VideoComm视频通信控件，集成高性压缩算法，实时传输协议，支持一对一(点对点)，一对多（广播式）等方式的的实时视频通信，视频画面清晰流畅！使用简单方便！ VideoComm视频通信控件适用于VC＋＋、VB、dot Net平台、C++Builder、Delphi、易语言、网页应用程序等各种常见的开发平台。
标签： ViedeoComm VideoComm 3.0 视频通信
上传时间： 2014-01-27
上传用户：lgnf
MATLAB的SVM算法实现，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.
上传时间： 2013-12-20
上传用户：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).
标签： column-weight girth-twelve constructs The
上传时间： 2016-11-01
上传用户：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
标签： rows The algorith distance
上传时间： 2014-01-15
上传用户：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.
标签： illustrates elimination Gaussian pivoting
上传时间： 2016-11-09
上传用户：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.
标签： illustrates elimination Gaussian pivoting
上传时间： 2014-01-21
上传用户：lxm
