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, ...