Title :
Tomography time-frequency transform
Author :
Zhang, Feng ; Bi, Guoan ; Chen, Yan Qiu
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fDate :
6/1/2002 12:00:00 AM
Abstract :
The paper shows that the fractional Fourier transform (FRFT) of a signal is the Radon transform of the time-frequency distribution of the same signal. Therefore, a time-frequency distribution known as the tomography time-frequency transform (TTFT) is defined as the inverse Radon transform of the FRFT of the signal. Because the computation of the TTFT does not explicitly require any window or kernel function, high resolutions in both the frequency and time domains can be achieved. When the signal contains multiple components, the cross terms can be effectively removed by an adaptive filtering process that is applied on the FRFT rather than the final result. Therefore, distortions made by the filtering process on the desired signal components can be minimized
Keywords :
Fourier transforms; Radon transforms; adaptive filters; adaptive signal processing; filtering theory; signal representation; signal resolution; statistical analysis; time-frequency analysis; tomography; FRFT; Radon transform; TTFT; adaptive filtering; cross terms; distortion minimization; fractional Fourier transform; frequency domain; high signal resolution; inverse Radon transform; kernel function; nonstationary signals; time domain; time-frequency distribution; tomography time-frequency transform; Adaptive filters; Bismuth; Fourier transforms; Frequency domain analysis; Kernel; Signal analysis; Signal processing; Signal resolution; Time frequency analysis; Tomography;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2002.1003054