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:
May. 19, 2020

Filed:

Aug. 28, 2014
Applicant:

Rokio, Inc., Kentfield, CA (US);

Inventors:

Tyson J. Thomas, San Francisco, CA (US);

Kristopher Robert Buschelman, San Francisco, CA (US);

Frank G. Evans, Portland, OR (US);

Karl P. Geiger, Redwood City, CA (US);

Michael P. Kelley, Lake Oswego, OR (US);

Eric C. Schneider, Redwood City, CA (US);

Timothy J. Carruthers, San Carlos, CA (US);

Jeffrey Brian Adams, Belmont, CA (US);

Assignee:

Rokio, Inc., Kentfield, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 5/04 (2006.01); G06N 20/00 (2019.01); G06K 9/00 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06N 5/047 (2013.01); G06K 9/0053 (2013.01); G06K 9/6255 (2013.01); G06N 20/00 (2019.01);
Abstract

Methods, apparatuses and systems directed to pattern learning, recognition, and metrology. In some particular implementations, the invention provides a flexible pattern recognition platform including pattern recognition engines that can be dynamically adjusted to implement specific pattern recognition configurations for individual pattern recognition applications. In certain implementations, the present invention provides for methods and systems suitable for analyzing and recognizing patterns in biological signals such as multi-electrode array waveform data. In other implementations, the present invention also provides for a partition configuration where knowledge elements can be grouped and pattern recognition operations can be individually configured and arranged to allow for multi-level pattern recognition schemes. In other implementations, the present invention provides methods and systems for dynamic learning of patterns in supervised and unsupervised manners.


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