The module LSQ is for unconstrained linear least-squares fitting. It is
based upon Applied Statistics algorithm AS 274 (see comments at the start
of the module). A planar-rotation algorithm is used to update the QR-
factorization. This makes it suitable for updating regressions as more
data become available. The module contains a test for singularities which
is simpler and quicker than calculating the singular-value decomposition.
An important feature of the algorithm is that it does not square the condition
number. The matrix X X is not formed. Hence it is suitable for ill-
conditioned problems, such as fitting polynomials.
By taking advantage of the MODULE facility, it has been possible to remove
many of the arguments to routines. Apart from the new function VARPRD,
and a back-substitution routine BKSUB2 which it calls, the routines behave
as in AS 274.
EDB (Evan s Debugger) is a QT4 based binary mode debugger with the goal of having usability on par with OllyDbg. It uses a plugin architecture, so adding new features can be done with ease. The current release is for Linux, but future releases will target more platforms.
Release focus: Major feature enhancements
Changes:
A new disassembly engine. A bug that could cause crashing was fixed. There is a new flags breakdown in the register view, an environment view plugin, and improved analysis (including a good speed increase). A bug in QT where disabled events could be triggered has been worked around.
Feature selection is a preprocessing technique frequently used in data mining and machine learning tasks. It can reduce dimensionality, remove irrelevant data, increase learning accuracy, and improve results comprehensibility. FCBF is a fast correlation-based filter algorithm designed for high-dimensional data and has been shown effective in removing both irrelevant features and redundant features
This library implements the KLT Tracking algorithm [2004] for Feature Tracking in Video useful in computer vision tasks like object recognition, image indexing, tracking and structure from motion. This implementation uses programmable Graphics Hardware to achieve considerable speedup in the running time of the GPU-based implementation.
This library implements the KLT Tracking algorithm [2004] for Feature Tracking in Video useful in computer vision tasks like object recognition, image indexing, tracking and structure from motion. This implementation uses programmable Graphics Hardware to achieve considerable speedup in the running time of the GPU-based implementation.
