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]
The toolbox solves a variety of approximate modeling problems for linear static models. The model can be parameterized in kernel, image, or input/output form and the approximation criterion, called misfit, is a weighted norm between the given data and data that is consistent with the model. There are three main classes of functions in the toolbox: transformation functions, misfit computation functions, and approximation functions. The approximation functions derive an approximate model from data, the misfit computation functions are used for validation and comparison of models, and the transformation functions are used for deriving one model representation from another.
KEYWORDS: Total least squares, generalized total least squares, software implementation.
ClustanGraphics聚類分析工具。提供了11種聚類算法。
Single Linkage (or Minimum Method, Nearest Neighbor)
Complete Linkage (or Maximum Method, Furthest Neighbor)
Average Linkage (UPGMA)
Weighted Average Linkage (WPGMA)
Mean Proximity
Centroid (UPGMC)
Median (WPGMC)
Increase in Sum of Squares (Ward s Method)
Sum of Squares
Flexible (ß space distortion parameter)
Density (or k-linkage, density-seeking mode analysis)
There a t least five Request for Enhancement s (RFE) in the JavaSoft bug database related to Mouse Wheel support in Java. One of the RFE s BugID #4202656 has 281 votes from developers requesting Sun for a fix. Sun has finally agreed to support this feature in JDK 1.4 codenamed Merlin accroding to the BugID #4289845 in its bug database.
The inverse of the gradient function. I ve provided versions that work on 1-d vectors, or 2-d or 3-d arrays. In the 1-d case I offer 5 different methods, from cumtrapz, and an integrated cubic spline, plus several finite difference methods.
In higher dimensions, only a finite difference/linear algebra solution is provided, but it is fully vectorized and fully sparse in its approach. In 2-d and 3-d, if the gradients are inconsistent, then a least squares solution is generated
