Online kernel density estimation using fuzzy logic. Issue 8 (1st October 2015)

• Record Type: Journal Article
• Authors: Zarch, Majid Ghaniee; Alipouri, Yousef; Poshtan, Javad
• Is Part Of: IET signal processing. Volume 9:Issue 8(2015)
• Page Start: 579
• Page End: 586
• Publication Date: 2015-10-01
• Subjects: fuzzy logic -- Gaussian processes -- mixture models -- risk analysis; online kernel density estimation -- fuzzy logic -- fuzzy method -- kernel density function online estimation -- Gaussian mixture model -- fuzzy algorithm -- defuzzifier operator -- observed data -- risk function -- fine tuning parameters -- temporal constraints; Signal processing -- Periodicals; 621.3822
• DOI: 10.1049/iet-spr.2014.0502
• Languages: English
• ISSNs: 1751-9675

Abstract

Abstract : In this paper, a fuzzy method is proposed to estimate kernel density function online. To achieve this goal, Gaussian mixture model is generated by the fuzzy algorithm. Defuzzifier operator is modified to make it suitable for this application. Means and variances of the model are adapted using observed data in each new sample. Then, rule weights are tuned by minimising the expected L 2 risk function of the estimated and true PDFs. In contrast to the existing approaches, our approach does not require fine‐tuning parameters for a specific application, specific forms of the target distributions are not assumed, and temporal constraints are not considered on the observed data. The algorithm is simple and easy to use. Simulation results show the capability of the proposed algorithm in online and accurate estimation of kernel density function.