Waterfilling algorithm (from [Palomar and Fonollosa, Trans-SP2004]) to compute:
pi = (mu*ai - bi)^+
sum(pi) = Pt
By Daniel Perez Palomar (last revision: May 10, 2004).
Kalman filter toolbox written by Kevin Murphy, 1998.
See http://www.ai.mit.edu/~murphyk/Software/kalman.html for details.
Installation
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1. Install KPMtools from http://www.ai.mit.edu/~murphyk/Software/KPMtools.html
3. Assuming you installed all these files in your matlab directory, In Matlab type
addpath matlab/KPMtools
addpath matlab/Kalman
Demos
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See tracking_demo.m for a demo of 2D tracking.
See learning_demo.m for a demo of parameter estimation using EM.
較早版本的kalman濾波matlab源碼，適合研讀。
