Thanks to their capability to cover large areas, in all weather conditions, during the day as well as during the night, spaceborne Synthetic Aperture Radar (SAR) techniques constitute an extremely promising alternative to traditional surveillance methods. Nevertheless, in order to assure further usability of SAR images, specific data mining methods are still to be developed to provide an effici...

Yan Zhao 1,2,*, Zhimin Li 1 and Yonghui Nie 3 1 Department of Electrical Engineering, Harbin Institute of Technology, Harbin 150001, China; [email protected] 2 Department of Power Transmission and Transformation Technology College, Northeast Dianli University, Jilin 132012, China 3 Academic Administration Office, Northeast Dianli University, Jilin 132012, China; [email protected] * Corresp...

This is a very brief introduction on the basic concepts of wavelet transform and its applications. It is certainly not possible to present comprehensive details for wavelets in a short time, only an attempt to interject some underlying features to engineers who are not yet familiarize with wavelet transform on what makes wavelet one of the most exciting useful tools as well as research areas to...

The fractional Fourier transform is a new concept in the theory of time-frequency representations. Closely linked to the Wigner distribution through the Radon transform, it introduces frequency-time hybrid domains in which the signal and the noise could be interwoven differently than in either the time or the frequency domain. The fractional transform breaks down a signal into elementary chirp ...

The uncertainty principles of the 1-D fractional Fourier transform and the 1-D linear canonical transform have been derived. We extend the previous works and discuss the uncertainty principle for the two-dimensional affine generalized Fourier transform (2-D AGFFT). We find that derived uncertainty principle of the 2-D AGFFT can also be used for determining the uncertainty principles of many 2-D...

This paper proposes time-frequency analysis of EEG spectrum and wavelet analysis in EEG de-noising. In this paper, the basic idea is to use the characteristics of multi-scale multi-resolution, using four different thresholds to wipe off interference and noise after decomposition of the EEG signals. By analyzing the results, understanding the effects of four different methods, it comes to a conc...

In this paper, a new adaptive Fourier decomposition (AFD) based time-frequency speech analysis approach is proposed. Given the fact that the fundamental frequency of speech signals often undergo fluctuation, the classical short-time Fourier transform (STFT) based spectrogram analysis suffers from the difficulty of window size selection. AFD is a newly developed signal decomposition theory. It i...

A procedure for logo watermarking of speech signals is proposed. In order to take full advantage of both time and frequency domain, we have used joint time-frequency representation of speech signal, which provides a more comprehensive information compared to each domain individually. Time-frequency based selection of the Discrete Fourier Transform (DFT) coefficients is used for logo embedding. ...

In this paper, we consider multiple signals sharing same instantaneous frequencies. This kind of data is very common in scientific and engineering problems. To take advantage of this special structure, we modify our data-driven time-frequency analysis by updating the instantaneous frequencies simultaneously. Moreover, based on the simultaneously sparsity approximation and fast Fourier transform...

The determination of probability of neurotransmitter release from neuronal release sites and their electrical characterization is an issue of central interest in neurophysiology. For autonomic nerves, this can be done by analysing the inflexions in the rising phases of the evoked junction potentials (EIPs) recorded from smooth muscle. Since these inflexions contain time-varying frequency inform...