The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 27, 2011

Filed:

Oct. 13, 2006
Applicants:

Erik Ordentlich, San Jose, CA (US);

Marcelo J. Weinberger, San Jose, CA (US);

Itschak Weissman, Menlo Park, CA (US);

Gadiel Seroussi, Cupertino, CA (US);

Inventors:

Erik Ordentlich, San Jose, CA (US);

Marcelo J. Weinberger, San Jose, CA (US);

Itschak Weissman, Menlo Park, CA (US);

Gadiel Seroussi, Cupertino, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H03D 1/04 (2006.01);
U.S. Cl.
CPC ...
Abstract

In various embodiments of the present invention, optimal or near-optimal multidirectional context sets for a particular data-and/or-signal analysis or processing task are determined by selecting a maximum context size, generating a set of leaf nodes corresponding to those maximally sized contexts that occur in the data or signal to be processed or analyzed, and then building up and concurrently pruning, level by level, a multidirectional optimal context tree constructing one of potentially many optimal or near-optimal context trees in which leaf nodes represent the context of a near-optimal or optimal context set that may contain contexts of different sizes and geometries. Pruning is carried out using a problem-domain-related weighting function applicable to nodes and subtrees within the context tree. In one described embodiment, a bi-directional context tree suitable for a signal denoising application is constructed using, as the weighting function, an estimated loss function.


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