Sparse representation method for on-line data collection of power

A technology of sparse representation and data collection, applied in the field of sparse representation, it can solve the problems of inability to solve sparse coding easily, spend a lot of time, and slow calculation speed, so as to reduce storage requirements, reduce storage space, and achieve the effect of compression

Inactive Publication Date: 2016-01-27
GLOBAL ENERGY INTERCONNECTION RES INST CO LTD +2
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  • Abstract
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Problems solved by technology

However, the biggest problem faced by the traditional sparse coding technology is poor real-time performance, slow calculation speed, it takes a lot of time to process the data, and it is not easy to solve the sparse coding in the face of big data.

Method used

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  • Sparse representation method for on-line data collection of power
  • Sparse representation method for on-line data collection of power
  • Sparse representation method for on-line data collection of power

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Embodiment Construction

[0028] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0029] The sparse coding model is an effective representation method for signals, and the coding model is:

[0030] w = arg m i n w 1 2 | | y - Φ * w | | 2 2 + λ | | w | | 1

[0031] where y∈R n is the target vector matrix, the matrix Φ∈R n×m is the set used for vector matrix sparse representation, m is the number of atoms in the set, w∈R m is the sparse coding coefficient vector, λ is the step size of the vector, R n×m is a vector matrix of n rows and m columns of data samples. The sol...

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Abstract

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.

Description

technical field [0001] The invention relates to a sparse representation method, in particular to a sparse representation method for online data collection of electric power. Background technique [0002] In today's society, the importance of data is gradually emerging, and it has become an important basis for the company's overall and comprehensive analysis. With the advancement of science and technology, people have more and more channels for obtaining information, and more and more data resources have been accumulated. The data volume of many Internet companies in a single day has reached hundreds of GB, and even more, it has reached TB (1TB) =1024GB) level. Traditional databases have been unable to meet such huge data storage requirements. In the current big data background where the amount of data is exploding, the emergence of sparse coding has successfully realized data compression and solved a series of problems such as large data storage volume and high hardware re...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/06
Inventor 周爱华孟祥君丁杰朱力鹏胡斌饶玮潘森
Owner GLOBAL ENERGY INTERCONNECTION RES INST CO LTD
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