GitHub - iron76/bnt_time_varying: Maximum-a-posteriori dynamic estimation for linkwise dynamic quantities

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Maximum-a-posteriori dynamic estimation for linkwise dynamic quantities

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Name		Name	Last commit message	Last commit date
Latest commit History 401 Commits
examples		examples
experiments		experiments
extern		extern
robot_models		robot_models
src		src
tests		tests
.gitattributes		.gitattributes
.gitignore		.gitignore
COPYRIGHT		COPYRIGHT
INSTALL		INSTALL
README		README
install.sh.template		install.sh.template

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This is a code to be used with the BNT toolbox for matlab by Kevin Murphy. 
The original toolbox can be downloaded from (https://code.google.com/p/bnt/).
The plugin in this repository modifies the EM estimation procedure  
described in www.ai.mit.edu/~murphyk/Papers/learncg.pdf
The modifications allow to estimate the variance matrices $\Simga_i$
by assuming that $B_i$ is known but time-varying in the sense that
its value is a function of t, i.e. B_{i,t} in equation (1).

DEPENDENCIES
 
 Currently the dependencies are (a) BNT toolbox and (b) FEATHERSTONE toolbox:
(0.a) https://github.com/bayesnet/bnt.git
(0.b) http://royfeatherstone.org/spatial/v2/spatial_v2.zip

DOCUMENTATION 

If you want to understand the code in bnt_time_varying, you should understand
how to use the BNT and SpatialV2 libraries, that are used in all the code. 
Nice entry points for this libraries are: 
 * SpatialV2 : http://royfeatherstone.org/spatial/v2/index.html
 * BNT       : http://bnt.googlecode.com/svn/trunk/docs/usage.html