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K-rank criterion multi-link data fusion algorithm based on credibility weighting

A technology of data fusion and trust, which is applied in computing, wireless communication, computer components, etc., can solve problems such as lack of correlation, and achieve the effect of improving recognition accuracy

Inactive Publication Date: 2020-08-07
LIAONING TECHNICAL UNIVERSITY
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The object of the present invention is to provide the multi-link data fusion algorithm based on the K-rank criterion weighted by the degree of trust, to solve the problem that there is no correlation in the above-mentioned background technology

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  • K-rank criterion multi-link data fusion algorithm based on credibility weighting
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  • K-rank criterion multi-link data fusion algorithm based on credibility weighting

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Embodiment Construction

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0025] see figure 1 , the present invention provides a technical solution: based on the K-rank criterion multi-link data fusion algorithm weighted by trust degree, the steps are as follows:

[0026] A), Trust degree vector initialization: There are n WiFi links between the transmitter and the receiver, and the trust degree vectors of these links are initialized as ω={ω t =0|t=1,2,...,n}, ω t is the trust degree corresponding to the t-th WiFi link when perfo...

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Abstract

The invention discloses a K-rank criterion multi-link data fusion algorithm based on credibility weighting, which comprises the following steps: A) initializing credibility vectors: providing n WiFi links between a transmitter and a receiver, and initializing the credibility vectors of the links as omega = {omega t = 0 | t = 1, 2,..., n}; and B) training a model: setting a training data set as S and the number of contained samples as M, extracting the characteristics of the t-th WiFi link of all samples in the training data set S to obtain a set S', and training the model by adopting a cross validation thought. By the method, data from a plurality of links is fused by utilizing a K-rank criterion algorithm, so that CSI changes on different links have correlation, and therefore, the human body behavior recognition of the CSI of all the links is improved, and the recognition accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of human behavior recognition, and in particular relates to a K-rank criterion multi-link data fusion algorithm based on trust degree weighting. Background technique [0002] The K-rank criterion is widely used in radio spectrum sensing, and its central idea is the large number criterion. In a certain sensing space, when there are N identical sensing nodes in the same external environment performing sensing independently of each other, if a sensing result If the number of D exceeds K, it is judged that the final result of perception is D. [0003] Human behavior can be recognized using a single WiFi link, although there are multiple WiFi links between the transmitter and receiver. However, there are two limitations in single link based identification. First, signal propagation is affected by multipath effects, and the obtained CSI is a combination of signals reflected by different human body parts through ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W24/08G06K9/62
CPCH04W24/08G06F18/254
Inventor 李新春牛震亮
Owner LIAONING TECHNICAL UNIVERSITY