The LZW compression class i mplemented as a fixed length code which you can specify, the huffman algorithm implementation encodes a byte into a variable length bit array. Both of them can work with streams
The tca package is a Matlab program that implements the tree-dependent
component analysis (TCA) algorithms that extends the independent
component analysis (ICA), where instead of looking for a linear transform
that makes the data components independent, we are looking for components
that can be best fitted in a tree structured graphical model. The TCA model
can be applied in any situation where the data can be assumed to have been
transformed by an unknown linear transformation.
Answering Queries using views is an article that contains an introduction to the theory and some algorithms, examples for the queries that uses views to resolve some problems. Also this article have a large references for more information about this subject.
This contribution provides functions for finding an optimum parameter set using the evolutionary algorithm of Differential Evolution. Simply speaking: If you have some complicated function of which you are unable to compute a derivative, and you want to find the parameter set minimizing the output of the function, using this package is one possible way to go.
The code performs a number (ITERS) of iterations of the
Bailey s 6-step FFT algorithm (following the ideas in the
CMU Task parallel suite).
1.- Generates an input signal vector (dgen) with size
n=n1xn2 stored in row major order
In this code the size of the input signal
is NN=NxN (n=NN, n1=n2=N)
2.- Transpose (tpose) A to have it stored in column
major order
3.- Perform independent FFTs on the rows (cffts)
4.- Scale each element of the resulting array by a
factor of w[n]**(p*q)
5.- Transpose (tpose) to prepair it for the next step
6.- Perform independent FFTs on the rows (cffts)
7.- Transpose the resulting matrix
The code requires nested Parallelism.
