Difference between revisions of "Lecture 16 - Parzen Window Method and K-nearest Neighbor Density Estimate OldKiwi" - Rhea

Revision as of 21:13, 16 March 2008

.. |Rn| image:: tex

alt: tex: R^n

.. |Parzen_ex| image:: tex

alt: tex: \varphi(\vec{u})=\frac{1}{(2\pi)^{\frac{n}{2}}}exp(\frac{-||\vec{u}||^2}{2})

Example of a useful Parzen window function in |Rn|: |Parzen_ex|

.. image:: Lec16_pw_pic1.PNG

This function has zero mean, H variance, an n-dimensional density, and is not compactly supported.

@@ Line 3: / Line 3: @@
 [http://balthier.ecn.purdue.edu/index.php/ECE662#Class_Lecture_Notes Class Lecture Notes]
-`Parzen Window <https://engineering.purdue.edu/people/mireille.boutin.1/ECE301kiwi/PazenWindow>`_ (Continued from [Lecture 14] and [Lecture 15])
 .. |Rn| image:: tex
-  :alt: tex: R^n
+:alt: tex: R^n
 .. |Parzen_ex| image:: tex
-  :alt: tex: \varphi(\vec{u})=\frac{1}{(2\pi)^{\frac{n}{2}}}exp(\frac{-||\vec{u}||^2}{2})
+:alt: tex: \varphi(\vec{u})=\frac{1}{(2\pi)^{\frac{n}{2}}}exp(\frac{-||\vec{u}||^2}{2})
 Example of a useful Parzen window function in |Rn|:  |Parzen_ex|