NDLI: Clustering Gaussian mixture reduction algorithm based on fuzzy adaptive resonance theory for extended target tracking

Content Provider	IET Digital Library
Author	Zhang, Yongquan Ji, Hongbing
Abstract	This study presents a global Gaussian mixture reduction (GMR) algorithm via clustering, which is based on a fuzzy adaptive resonance theory (FART) neural network architecture. Therefore the authors call the proposed algorithm as GMR based on the fuzzy ART (GMR-FART) in this study. The architecture of GMR-FART is similar to that of the FART, however, its choice function, match function and learning update equations are characterised by features of Gaussian mixture (GM). The proposed algorithm automatically forms categories (i.e. the reduced GM components) via a feedback mechanism. The performance of GMR-FART is evaluated by the normalised integrated squared distance measure which describes the deviation between the original and the reduced GM. The proposed algorithm is tested on both one-dimensional (1D) and 4D simulation examples, and the results show that the proposed algorithm can accurately approximate the original mixture and requires less computational burden, and is useful in extended target tracking.
Starting Page	536
Ending Page	546
Page Count	11
ISSN	17518784
Volume Number	8
e-ISSN	17518792
Issue Number	Issue 5, Jun (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/8/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2013.0254
Journal	IET Radar, Sonar & Navigation
Publisher Date	2014-01-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	1D Simulation 4D Simulation ART Neural Nets Clustering Gaussian Mixture Reduction Algorithm Combinatorial Mathematics Data Handling Technique Digital Signal Processing Distance Measurement Extended Target Tracking FART Feedback Mechanism Fuzzy Adaptive Resonance Theory Fuzzy Set Theory Gaussian Processes GMR Knowledge Engineering Technique Learning in AI Learning Update Equation Match Function Neural Computing Technique Neural Network Architecture Normalised Integrated Squared Distance Measurement One-dimensional Simulation Pattern Clustering Recurrent Neural Nets Signal Processing And Detection Statistics Target Tracking
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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