Abstract Space-time and time-varying metastructures have attracted a lot of research interest in recent years. On the other hand, digital programmable metasurfaces also gained great attention owing to their powerful capabilities controlling electromagnetic (EM) fields waves real time, which is very suitable for implementing spatiotemporal modulations manner. Accordingly, space-time-coding (STC)...

We develop a novel measure of joint time-frequency localization applicable to equivalence classes of finite-length discrete signals, which are of increasing importance in modern signal and image processing applications. Like the wellknown Heisenberg-Weyl uncertainty principle that quantifies joint localization for continuous signals, this new measure is translation invariant and admits an intui...

Traditional modal analysis methods use either time domain or frequency domain approaches. Because vibration signals are generally non-stationary, time and frequency information is needed simultaneously in many cases. This paper presents an overview of the applications of joint time-frequency methods for modal analysis. Since a joint time-frequency analysis can decouple vibration modes, it has a...

We have developed a new expansion’ we call the “chirplet transform”. It has been successfully applied to a wide variety of signal processing applications including radar[l] and image processing. There has been a recent debate as to the relative merits of an affine-in-time (wavelet) transform and the classical Short Time Fourier Transform (STFT), for the analysis of non-stationary phenomena. Chi...

The time-frequency content of a signal can be measured by the Gabor transform or windowed Fourier transform. This is a function defined on phase space that is computed by taking the Fourier transform of the product of the signal against a translate of a fixed window. The problem of finding signals with Gabor transform that are maximally concentrated within a given region of phase space is discu...

In this paper, we propose a new residual analysis method using Fourier series transform into fuzzy time series model for improving the forecasting performance. This hybrid model takes advantage of the high predictable power of fuzzy time series model and Fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...

This paper describes how a signal can be written as a weighted sum of certain "elementary" synthesizing functions, which are the dilated and translated versions of a single parent function. The weighting constants in this sum define a transform of the signal. This is much like Fourier analysis except that a wide choice is permitted in the selection of a set of synthesizing functions. Moreover, ...

This paper serves the idea of applying joint time-frequency representations in electrical engineering. Main directions of researches are concentrated around Cohen’s class of transformation which gives some possibilities of adaptation for analysed signal by choosing appropriate kernel function. Additionally, novel approach delivered by S-transform is also introduced. In order to investigate the ...

An oversampled discrete-time Gabor transform (DTGT) has inherent redundancy for signal representation in the joint time-frequency domain. In the proposed multiple-access communication system, this redundancy is used to separate different signals. The DTGTs of all users' signals are transmitted in the same time slots and frequency bands. The DTGTs of the signals can be separated if the analysis ...