A method and system for generating sensor data based on generating countermeasure network

A data generation and generator technology, applied in the fields of ubiquitous computing, deep learning and machine learning, which can solve the problems of vanishing gradients, difficult to deal with long-term dependencies, development and application limitations, etc., to improve accuracy and performance, and promote further development. Effects of development and application

Active Publication Date: 2018-12-25
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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Problems solved by technology

However, each hidden unit of the traditional cyclic neural network only contains simple operations such as Tanh or ReLU, and there are defects such as gradient disappearance / gradient explosion in practical applications, so it is difficult to deal with long-term dependence problems, which leads to its use in the field of sensor data. The development and application of the

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  • A method and system for generating sensor data based on generating countermeasure network
  • A method and system for generating sensor data based on generating countermeasure network
  • A method and system for generating sensor data based on generating countermeasure network

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[0044] In order to make the purpose, technical solution and advantages of the present invention clearer, the sensor data synthesis method and system based on the generative confrontation network proposed by the present invention will be further described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation methods described here are only used to explain the present invention, and are not intended to limit the present invention.

[0045] In view of the variability of sensor data at any time and the high precision requirements, the traditional generative adversarial network methods and models suitable for image data generation cannot be directly applied to the generation of sensor data, which also determines the construction of corresponding generative Difficulty of adversarial network method models. Therefore, it is a complex and difficult forward-looking technical problem to study an effective generative advers...

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Abstract

The invention relates to a sensor data generation method based on generating an antagonism network. The method comprises the following steps: a model construction step of constructing a generation antagonism network model by using real data through a neural network model, wherein the generation antagonism network model comprises a generator and a discriminator; a model training step of training the generator and the discriminator with a countermeasure game mechanism and performing iteration until the data obtained from the generator satisfies an evaluation criterion; a data generation step ofgenerating composite data by the generator through the countermeasure network model.

Description

technical field [0001] The invention relates to the fields of pervasive computing, deep learning and machine learning, and in particular to a method and system for generating sensor data based on generative confrontation networks. Background technique [0002] Generative adversarial networks (GANs) were first proposed by IanGoodFellow in 2014. The framework of this method is mainly composed of a generation network (generator) and a discriminant network (discriminator). Its goal is mainly to assist training through the discriminant network. A Generative Network that Accurately Learns the Distribution Properties of Raw Data. The generation network and the discriminant network continue to improve their performance in the mutual game and confrontation, that is, the generator continues to evolve to generate synthetic data that is closer to real data, and at the same time, the discriminator also continues to evolve to improve its ability to distinguish between true and false data ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/20G06F18/2431G06F18/251G06F18/214
Inventor 陈益强王记伟谷洋肖云龙潘浩楠
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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