Sparse representation method for on-line data collection of power

Sparse representation method for on-line data collection of power

The invention discloses a sparse representation method for the on-line data collection of power, and the method comprises the following steps: (1) building a sparse coding mode, and initializing a zero vector; (2) randomly sampling a data sample for iteration; (3) updating a sparse coding coefficien...

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Hauptverfasser: DING JIE, ZHU LIPENG, ZHOU AIHUA, RAO WEI, MENG XIANGJUN, PAN SEN, HU BIN
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:The invention discloses a sparse representation method for the on-line data collection of power, and the method comprises the following steps: (1) building a sparse coding mode, and initializing a zero vector; (2) randomly sampling a data sample for iteration; (3) updating a sparse coding coefficient; (4) calculating an approximation error; (5) judging the algorithm convergence. The method is used for the research of big data of power based on a random gradient descent algorithm, can quickly and effectively process data, greatly improves the solving efficiency, also can effectively solve a sparse coding coefficient, achieves the compression of big-data sparse coding, reduces the storage space, and reduces the storage requirements for hardware.