A method to suppress the end-effects of emd based on lstm network

An endpoint effect and network technology, applied in the field of signal processing, can solve problems such as failure, impact of prediction results, and great influence of time-frequency analysis methods, and achieve the effects of improving accuracy, solving the problem of endpoint effects, and solving endpoint effects

Active Publication Date: 2022-07-01
东北大学秦皇岛分校
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Problems solved by technology

The endpoint effect in cubic spline interpolation and Hilbert transform has a great influence on the time-frequency analysis method based on EMD. If this problem is not handled properly, the effect of this time-frequency analysis method will be affected or invalidated.
However, in its application, the selection of LSTM network time step parameters has a great influence on the prediction results, so determining the LSTM time step to improve the prediction performance of data is the key issue to suppress the EMD endpoint effect

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  • A method to suppress the end-effects of emd based on lstm network
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  • A method to suppress the end-effects of emd based on lstm network

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[0038] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present invention.

[0039] Embodiments of the present invention:

[0040] An EMD endpoint effect suppression method based on LSTM network, such as figure 1 shown, including the following steps:

[0041] S1.1, use the wireless measurement equipment to collect the mixed sound signals of multiple indoor mechanical devices. Let x(t) be the mixed signal at time t, and the mixed signal x(t) is mixed with multiple devices. The sound and noise of the mixed signal x(t) ...

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Abstract

The invention belongs to the technical field of signal processing, and in particular relates to a method for suppressing EMD end point effect based on LSTM network. The method effectively combines the prediction of the signal by the LSTM network and the application of EMD decomposition in the single-channel blind source separation technology, and finds the time step of the LSTM network according to the characteristics of the signal, which effectively improves the prediction accuracy, thereby effectively It solves the end effect problem of EMD method in single-channel blind source separation, and achieves good results in solving the sound separation problem in complex factory environment. This method can effectively solve the problem of end-effects in nonlinear non-stationary time series analysis, and can be applied to the separation of single-channel blind source mixed signals.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a method for suppressing EMD end point effects based on an LSTM network. Background technique [0002] Blind source separation technology refers to the process of separating each source signal by only using the observed signal according to the statistical characteristics of the source signal when both the transmission channel and the source signal are unknown. In fact, most of the collected signals are single-channel signals, and single-channel blind source separation is an extreme case of the underdetermined blind source separation problem. It only uses the characteristic information of a single-channel observation signal to separate multi-channel source signals. It is very difficult to solve. In 1998, Norden E. Huang of NASA first proposed a signal processing method to first perform empirical mode decomposition on a column of time series data, and then pe...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L25/30G10L25/51G06N3/04
CPCG10L25/30G10L25/51G06N3/044G06N3/045
Inventor 刘福来胡忠意杜瑞燕张艾怡黄彩梅徐嘉良
Owner 东北大学秦皇岛分校
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