Sliding Discrete Linear Canonical Transform

Autor: Yan-Nan Sun, Bing-Zhao Li
Rok vydání: 2018
Předmět:
Zdroj: IEEE Transactions on Signal Processing. 66:4553-4563
ISSN: 1941-0476
1053-587X
Popis: The linear canonical transform (LCT) has been shown to be one of the most powerful tools in signal processing, and in this paper, we propose an adaptive approach for the computation of the discrete LCT (DLCT), termed the sliding discrete linear canonical transform (SDLCT). First, we introduce a scheme for the single-point DLCT, which can effectively calculate a single or a few linear canonical spectra. Second, the SDLCT is proposed based on an iterative algorithm to meet the requirements of online spectral analysis when only a subset of $N$ frequencies are required from an $\tilde{N}\hbox{--}$ point discrete LCT ( $N\leq \tilde{N}$ ). The additivity and reversibility properties of the proposed algorithms are also discussed in detail. Third, the DLCT convolution operation is obtained to reduce the spectral leakage of the proposed algorithm, and time-domain windowing is implemented via frequency-domain convolution. Finally, we present two methods to assess performance with regard to computational complexity and precision and to show the correctness of the derived results.
Databáze: OpenAIRE