Inference of Parameterized Fourier Transforms
Journal
2025 IEEE International Symposium on Circuits and Systems (ISCAS)
Start Page
1-5
Date Issued
2025-05-25
Author(s)
Abstract
This paper presents new theoretical and application aspects on inferring the parameters in integral transforms. An integral transform, e.g., the linear canonical transform (LCT), usually has many parameters. It is a difficult issue to find the optimal parameters of the integer transform. In this work, we propose a generalized inference method to determine the optimal parameters of the LCT and the fractional Fourier transform (FrFT). With proper design of object functions, optimal parameter estimation can be performed effectively and automatically. The LCT with the optimal parameter set can well represent a complex signal and minimize the energy outside of the low-frequency band in terms of the ℒ1 or the ℒ2 norm. It is applicable in signal processing, filter design, system modeling, and machine learning.
Publisher
IEEE
Type
conference paper