Unconstrained linear combination of even mirror Fourier non-linear filters
IET Signal Processing, ISSN: 1751-9683, Vol: 8, Issue: 6, Page: 612-621
2014
- 3Citations
- 5Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
In this study, the unconstrained linear combination of the outputs of even mirror Fourier non-linear filters is considered. These filters are new members of the class of causal, shift-invariant, finite-memory and linear-in-the parameters non-linear filters. Their name derives from the even symmetry of their trigonometric basis functions. Even mirror Fourier non-linear filters are universal approximators for causal, time invariant, finite-memory and continuous non-linear systems. Moreover, their basis functions are mutually orthogonal for white uniform input signals in the interval [-1, +1]. The authors show in this study how to exploit these characteristics, in the framework of the unconstrained linear combination of non-linear filters, for modelling unknown non-linear systems. In particular, they show that the filters whose outputs are combined can be adapted avoiding the choice of the step sizes, by using a simple algorithm presented in this study. The analysis of the proposed structures is accompanied by a set of simulation results that confirm the good performance obtained in different situations.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84928255847&origin=inward; http://dx.doi.org/10.1049/iet-spr.2013.0256; https://onlinelibrary.wiley.com/doi/10.1049/iet-spr.2013.0256; https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-spr.2013.0256; https://onlinelibrary.wiley.com/doi/full-xml/10.1049/iet-spr.2013.0256; https://dx.doi.org/10.1049/iet-spr.2013.0256; https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-spr.2013.0256
Institution of Engineering and Technology (IET)
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know