ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical abstracts (MED dataset), that uses BIC to estimate the number of classes and produces keywords for each class. The icaML algorithm is used.
* A ncurses user interface.
* Network statistics to view the amount of packets and data in many
different protocols, interfaces and hosts.
* View what active TCP connections are on the network.
* View UDP packets.
* View and log ICMP packets.
* View and log the 48bit arp protocol.
And also view what make of network card is in each machine
* Multithreaded so that the user interface does not interfere with any of the packet
captureing methods.
* View and log the following user space protocols
FTP, POP3, HTTP
The original NuLib has been ported to many different systems. Version 3.2.5 is functionally similar to v3.2.4, but the source code and documentation were cleaned up by Devin Reade, making it easier to build. NuLib2 is generally superior, but NuLib does have the advantage of running under 16-bit MS-DOS and GS/OS.
Windowed-Burg method is made in order to improve the Clasical Burg method. Previously, I send the PBURGW.m file, but now I include also the ARBURGW.m algorithm and some NOTES-EXAMPLES to explain it and compare with the pburg.m algorithm from MATLAB.
