Title
Simultaneous Dft And Idft Through Widely Linear Clms
Abstract
Complex least mean square (CLMS) based adaptive computation of discrete orthogonal transforms has been extensively investigated in the literature. However, all of these results provide only a means for the calculation of either forward orthogonal transforms or their inverse orthogonal transforms, separately. In this work, a way to simultaneously calculate the discrete Fourier transform (DFT) and the inverse DFT (IDFT) is established via the widely linear (WL) signal processing framework. We show that by appropriately selecting the input vector and adaptation speed of the widely linear complex least mean square (WL-CLMS), the resulting spectrum analyzer is capable of simultaneously performing DFT and IDFT of the signal to be Fourier analyzed in both the block-based and online manners.
Year
DOI
Venue
2019
10.1109/icassp.2019.8683135
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
DFT, inverse DFT (IDFT), widely linear CLMS, recursive DFT and IDFT spectrum analyzer
Least mean squares filter,Signal processing,Inverse,Pattern recognition,Computer science,Algorithm,Fourier transform,Artificial intelligence,Discrete Fourier transform,Computation
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Xing Zhang174.89
Bruno Scalzo Dees222.06
Chunguo Li34810.72
Yili Xia424725.50
Luxi Yang51180118.08
Danilo Mandic61641173.32