Method, device and terminal equipment for extracting composition pattern of time series data
A technology of time series and extraction method, applied in the field of data processing, it can solve the problems of strong assumptions about the distribution characteristics of source data and the inability to take into account the local variation characteristics of the sequence.
Active Publication Date: 2022-07-05
SHENZHEN UNIV
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[0003] The traditional time series data analysis mainly focuses on the overall information of the time series in the time domain or frequency domain, and cannot take into account the local variation characteristics of the series; and the method of taking dynamic time warping DTW and autoregressive moving average model ARMA as examples also takes the time series into account. The data is inferred as a whole, and these methods generally use generative methods to model time series, and there are strong assumptions about the distribution characteristics of the source data.
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[0056] In the following description, for the purpose of illustration rather than limitation, specific details such as a specific system structure and technology are set forth in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
[0057] It is to be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described feature, integer, step, operation, element and / or component, but does not exclude one or more other The presence or addition of features, integers, steps, operations, elements, components and / or sets thereof.
[0...
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The present application is applicable to the technical field of data processing, and provides a method, device and terminal equipment for extracting the composition pattern of time series data. The above method for extracting the composition pattern of time series data includes: acquiring time series sample data; dividing the time series sample data forming a plurality of time series sample data segments; determining the subject distribution of the composition pattern of each of the time series sample data segments, and assigning the corresponding time series sample data segments with the subject distribution corresponding to the subject distribution based on the determined subject distribution model. The above method for extracting the composition pattern of time series data can effectively obtain the composition components of the time series, which is beneficial to extract the ROI of the region of interest required for research from the lengthy time series.
Description
technical field [0001] The present application belongs to the technical field of data processing, and in particular, relates to a method, device and terminal device for extracting a composition pattern of time series data. Background technique [0002] Time series data is data collected in chronological order to describe the state or degree of change of things or phenomena over time, such as electrocardiogram (ECG), electroencephalogram (EEG), current and voltage signals in manufacturing, stock trading K line, time domain waveform of voice signal, etc. Among them, the composition pattern of time series data is an important factor to understand the past behavior of time series data. [0003] The traditional time series data analysis mainly focuses on the overall information of the time series in the time domain or frequency domain, and cannot take into account the local variation characteristics of the sequence; while the methods such as dynamic time warping DTW and the auto...
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IPC IPC(8): G06F16/2458
CPCG06F16/2474G06F16/2465
Inventor 李国法陈耀昱赖伟鉴杨一帆李晓航林勇杰陈昕
Owner SHENZHEN UNIV