Invention Grant
- Patent Title: Decremental autocorrelation calculation for big data using components
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Application No.: US15986764Application Date: 2018-05-22
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Publication No.: US10659369B2Publication Date: 2020-05-19
- Inventor: Jizhu Lu
- Applicant: Jizhu Lu
- Applicant Address: US WA Redmond
- Assignee: CLOUD & STREAM GEARS LLC
- Current Assignee: CLOUD & STREAM GEARS LLC
- Current Assignee Address: US WA Redmond
- Main IPC: H04L12/813
- IPC: H04L12/813 ; H04L29/08 ; G06F16/955 ; G06F16/2458

Abstract:
The present invention extends to methods, systems, and computing system program products for decrementally calculating autocorrelation for Big Data. Embodiments of the invention include decrementally calculating one or more components of autocorrelation at a specified lag for an adjusted computation window based on the one or more components of an autocorrelation at the specified lag calculated for a previous computation window and then calculating the autocorrelation at the specified lag based on one or more of the decrementally calculated components. Decrementally calculating autocorrelation avoids visiting all data elements in the adjusted computation window and performing redundant computations thereby increasing calculation efficiency, saving computing resources and reducing computing system's power consumption.
Public/Granted literature
- US20180270158A1 DECREMENTAL AUTOCORRELATION CALCULATION FOR BIG DATA USING COMPONENTS Public/Granted day:2018-09-20
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