Signal reconstruction method based on generative adversarial network

A signal reconstruction and network technology, applied in biological neural network models, interference to communication, neural architecture, etc., can solve the problem of difficult to accurately extract and learn signal sequence characteristics, high similarity between signal and original signal, neural network layer gradient Disappearance and other problems, to achieve the effect of solving the difficulty of signal analysis, rich signal diversity, and improved similarity
CN108696331AActive Publication Date: 2018-10-23XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2018-10-23

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Abstract

The invention belongs to the technical field of radio signal reconstruction, and discloses a signal reconstruction method based on a generative adversarial network. The method includes the following steps: under the framework of the generative adversarial network, constructing a generator for generating a signal and a discriminator for judging whether the signal is real data, and updating and optimizing parameters of the generator through the cross training of the generator and the discriminator. The scheme of the invention is suitable for the signal reconstruction in a complex electromagneticenvironment, has the characteristics of simple operating process, high similarity of generated data and the like, and effectively overcomes the shortcomings of low similarity of generated samples andinsufficient sample diversity existing in a current signal reconstruction method; and the scheme of the invention proposes a method of implementing the signal reconstruction by using the generative adversarial network, the cross-game training of the generative adversarial network is adopted, signal features are extracted through the mapping of a network layer, the cumbersome and inefficient process of performing parameter measurement, feature extraction and the like on the signal can be eliminated, and the problem of difficulties in signal analysis in the complex electromagnetic environmentscan be solved.
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Description

technical field

[0001] The invention belongs to the technical field of communication countermeasures, in particular to a signal reconstruction method based on a generative countermeasure network. That is, based on the technology of generative confrontation network, a neural network that automatically generates signals is built as a generator and a discriminator to judge the quality of generated data, which is suitable for reconstructing signals that receive noise interference in electromagnetic environments. Background technique

[0002] At present, the existing technologies commonly used in the industry are as follows:

[0003] In the technical field of radio signal reconstruction, traditional signal reconstruction adopts a technical system based on parameter measurement, feature extraction, and signal reconstruction. This signal reconstruction system is relatively easy to reconstruct radio signals in an electromagnetic environment with low information density and few com...

Claims

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