This algorithm was developed by Professor Ronald L. Rivest of MIT and can be found presented in several languages. What I provide to you here is a C++ derivative of the original C implementation of Professor Rivets. The library code itself is platform-independant and has been tested in Redhat Linux. ...
This companion disc contains the source code for the sample
programs presented in INSIDE VISUAL C++ 5.0, as well as pre-
compiled copies of the programs.
To copy all of the sample code onto your hard disk, run the
SETUP.EXE program and follow the instructions that appear on
the screen. The sample c ...
A method is presented for augmenting an extended
Kalman filter with an adaptive element. The resulting estimator
provides robustness to parameter uncertainty and unmodeled
dynamics.
This companion disc contains the source code for the sample
programs presented in INSIDE VISUAL C++ 5.0, as well as pre-
compiled copies of the programs.
A general technique for the recovery of signi cant
image features is presented. The technique is based on
the mean shift algorithm, a simple nonparametric pro-
cedure for estimating density gradients. Drawbacks of
the current methods (including robust clustering) are
avoided. Feature space of any nat ...
The tool presented below tries to detect from remote if the target machine was compromised with the HACKER Defender rootkit. The tool connect to the remote host, and compares the reply to several known replies. The rootkits that can be detected by the tool are: HACKER Defender v1.0.0 and below.
This file contains the material presented as the first Embedded MATLAB webinar on the MathWorks web site on September 13, 2007.
It contains the PDF version of presentation slides and all necessary demonstration files (including MATLAB M-files and Simulink models).
