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• W3102497486 abstract "This letter exploits geometric (Clifford) algebra (GA) theory to devise and introduce a new adaptive filtering strategy. From a least-squares cost function, the gradient is calculated following results from geometric calculus (GC), the extension of GA to handle differential and integral calculus. The novel GA least-mean-squares (GA-LMS) adaptive filter, which inherits properties from standard adaptive filters and from GA, is developed to recursively estimate a rotor (multivector), a hypercomplex quantity able to describe rotations in any dimension. The adaptive filter (AF) performance is assessed via a 3-D point-clouds registration problem, which contains a rotation estimation step. Calculating the AF computational complexity suggests that it can contribute to reduce the cost of a full-blown 3-D registration algorithm, especially when the number of points to be processed grows. Moreover, the employed GA/GC framework allows for easily applying the resulting filter to estimating rotors in higher dimensions." @default.
• W3102497486 created "2020-11-23" @default.
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• W3102497486 date "2016-06-01" @default.
• W3102497486 modified "2023-09-26" @default.
• W3102497486 title "Geometric-Algebra LMS Adaptive Filter and Its Application to Rotation Estimation" @default.
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• W3102497486 doi "https://doi.org/10.1109/lsp.2016.2558461" @default.
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