Viral hashtags spread across a large population of Internet users very quickly. Previous studies use features mostly in an aggregate sense to predict the popularity of hashtags, for example, the total number of hyperlinks in early tweets adopting a tag. Since each tweet is time stamped, many aggregate features can be decomposed into fine-grained time series such as a series of numbers of hyperl...

Wind Energy is a useful resource for Renewable energy purpose. Wind speed plays a vital role for wind energy calculation of certain location. So, it is very much necessary to know the wind speed data characteristics. In this paper fourier and wavelet transform are applied to study the wind speed data. We have compared wind speed of winter with summer by taking their speed into account using var...

F005. Hubbard, B. B. [1998] The world according to wavelets the story of a mathematical technique in the making. 2 Edition, A K Peters. Qian, S. [2002] Introduction to time-frequency and wavelet transforms.

The information extraction capability of two widely used signal processing tools, Hilbert Transform (HT) and Wavelet Transform (WT), is investigated to develop a multi-class fault diagnosis scheme for induction motor using radial vibration signals. The vibration signals are associated with unique predominant frequency components and instantaneous amplitudes depending on the motor condition. Usi...

A signal-based pattern-recognition approach is used for structural damage diagnosis with a single or limited number of input/output signals. The approach is based on extraction of the features of the structural response that present a unique pattern for each specific damage case. In this study, frequency-based features and time-frequency-based features were extracted from measured vibration sig...

The S transform, which is introduced in this correspondence, is an extension of the ideas of the continuous wavelet transform (CWT), and is based on a moving and scalable localizing Gaussian window. It is shown here to have some desirable characteristics that are absent in the continuous wavelet transform. The S transform is unique in that it provides frequency-dependent resolution while mainta...

Although the discretized continuous wavelet transform enables the computation of the continuous wavelet transform by computers, it is not a true discrete transform. As a matter of fact, the wavelet series is simply a sampled version of the CWT, and the information it provides is highly redundant as far as the reconstruction of the signal is concerned. This redundancy, on the other hand, require...