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Title:
GLOBALLY OPTIMAL PARTICLE FILTERING METHOD AND GLOBALLY OPTIMAL PARTICLE FILTER
Document Type and Number:
WIPO Patent Application WO/2018/157699
Kind Code:
A1
Abstract:
A globally optimal particle filtering method and a globally optimal particle filter, which relate to the field of signal processing and which overcome the disadvantage wherein existing particle filters cause large deviations between sampled samples and true posterior probability density samples, effectively solving the problem of processing nonlinear and non-Gaussian signals by means of particle filtering. The main technical means is to construct a globally optimal particle filter by using Lamarck's genetic law of nature, comprising: generating an initial particle set; using unscented Kalman filtering to carry out importance sampling on the initial particle set to obtain sampled particles; carrying out floating point coding on each sampled particle to obtain an encoded particle set; configuring an initial population; using the initial population as an original experimental population, and sequentially performing a Lamarck rewrite operation, a real number decoding operation, and an elite retention operation; using an optimal candidate particle in real number form as a prediction sample for a subsequent time to obtain a state estimation value of a system. The present invention is suitable for machine learning.

Inventors:
LI, Lin (No.1, Daxue Rd. Songshan Lak, Dongguan Guangdong 8, 523808, CN)
LI, Yun (No.1, Daxue Rd. Songshan Lak, Dongguan Guangdong 8, 523808, CN)
Application Number:
CN2018/075151
Publication Date:
September 07, 2018
Filing Date:
February 02, 2018
Export Citation:
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Assignee:
DONGGUAN UNIVERSITY OF TECHNOLOGY (No.1, Daxue Rd. Songshan Lak, Dongguan Guangdong 8, 523808, CN)
LI, Lin (No.1, Daxue Rd. Songshan Lak, Dongguan Guangdong 8, 523808, CN)
LI, Yun (No.1, Daxue Rd. Songshan Lak, Dongguan Guangdong 8, 523808, CN)
International Classes:
H03H17/00
Foreign References:
CN101826852A2010-09-08
CN101710384A2010-05-19
CN101807900A2010-08-18
Other References:
LI, LIN ET AL.: "Particle Filter with Lamarckian Inheritance for Nonlinear Filtering", 2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC, 21 November 2016 (2016-11-21), pages 2852 - 2857, XP033007043
Attorney, Agent or Firm:
YOGO PATENT & TRADEMARK AGENCY LIMITED COMPANY (Room 4416, Block B Sinopec Tower,,No. 191 Tiyu West Rd., Tianhe Distric, Guangzhou Guangdong 0, 510620, CN)
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