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A Fast Algorithm for Computation of General Integer-Order Hankel Transforms

delete2025-01-01
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PRE
AI
A
Amitava Ghosh
A
Anindya Sundar Dhar
I
Indrajit Chakrabarti
DOI:10.1109/LSP.2025.3592107delete
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Abstract

Abstract

En 中文
The letter presents an improved algorithm for computation of general integer-order Hankel transforms, which is back-projection based. The original algorithm breaks the Hankel transform into an inverse fast Fourier transform and a discrete summation involving trigonometric terms (which is more computationally intensive). In this work, by varying the number of terms of the discrete summation with the transform order, the number of trigonometric computations and multiplications can be reduced drastically, which leads to overall computational complexity improvement. To be precise, the time complexity constant is reduced so much that our algorithm is faster than the state-of-the-art, while being O(N<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>). The algorithm has been simulated in MATLAB and a performance improvement of 6.04x in the discrete summation step (average case) over the original algorithm has been obtained. Finally, computational error of our proposed algorithm has been obtained, which is better than the baseline algorithm, and is comparable to the state-of-the-art.
Keywords:
Back-projection
computation time
error sources

Journal

IEEE Signal Processing Magazine cover
IEEE Signal Processing Magazine
IF:
9.6
Papers:
1.1W
Citations:
1.7W

Organization

I
indian institute of technology kharagpur
Scholars:
1.5K
Papers: 663
Citations: 0