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Dictionary learning method for polynomial phase signal denoising

A phase signal, dictionary learning technology, applied in the field of signal processing, can solve the problems of lack of adaptability, affecting the signal denoising effect, etc., to achieve the effect of reducing complexity and good denoising effect

Active Publication Date: 2021-04-06
CHONGQING COLLEGE OF ELECTRONICS ENG
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  • Claims
  • Application Information

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Problems solved by technology

The training data of the dictionary learning algorithm is divided into two types, one is data without noise, and the other is object data with noise; the former lacks adaptability, while the latter has good adaptability, but is affected by Noise has a great influence, which will affect the denoising effect of the signal

Method used

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  • Dictionary learning method for polynomial phase signal denoising
  • Dictionary learning method for polynomial phase signal denoising
  • Dictionary learning method for polynomial phase signal denoising

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Embodiment

[0048] The dictionary learning method of a kind of polynomial phase signal denoising of the present embodiment comprises the following steps:

[0049] S1. Establish the following formula:

[0050]

[0051]S2. Use the polynomial phase signal itself that needs to be denoised as the training signal, and construct the training signal set Y∈R according to the phase space reconstruction theory N×L , and at the same time take the K column of Y as the initialization dictionary D 0 ∈ R N×K , and standardize it. In this embodiment, standardization refers to the vector, that is, the l of each column in the K columns of Y is randomly taken 2 The norm is 1.

[0052] Each column in the initialization dictionary represents an atom, and K represents the number of atoms in the dictionary. Since a redundant dictionary is used, K>>N;

[0053] The set of trained signals Y∈R N×L , where L>>K, so we know that the coefficient matrix W∈R K×L .

[0054] Since the polynomial phase signal tha...

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Abstract

The invention relates to the technical field of signal processing, and particularly discloses a polynomial phase signal denoising dictionary learning method. The method comprises the following steps: constructing a trained signal set by taking a polynomial phase signal needing denoising as a trained signal; and denoising a single atom by using the improved power excitation forward neural network model. By adopting the technical scheme of the invention, the signal denoising effect can be improved.

Description

technical field [0001] The invention relates to the technical field of signal processing, in particular to a dictionary learning method for polynomial phase signal denoising. Background technique [0002] The polynomial phase signal has a wide range of applications in signal processing, such as communication systems, radar, sonar, etc. The application of sonar includes underwater detection of ships, and the third-order polynomial phase signal (CPS) is often used in radar signal processing. The echo phase of the target is modeled. [0003] Since polynomial phase signals are widely used in signal processing, it is very important to denoise polynomial phase signals. There are many common methods for signal denoising, such as wavelet-based denoising methods, signal denoising methods based on independent component analysis, signal denoising methods based on phase matching, and signal denoising methods based on sparse representation, etc., in Among these methods, since sparse re...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08G06F17/16
CPCG06N3/084G06F17/16G06N3/044G06F2218/04
Inventor 欧国建朱崇来
Owner CHONGQING COLLEGE OF ELECTRONICS ENG
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