We introduce the use of DCTNet, an efficient approximation and alternative to PCANet, for acoustic signal classification. In PCANet, the eigenfunctions of the local sample covariance matrix (PCA) are used as filterbanks for convolution and feature extraction. When the eigenfunctions are well approximated by the Discrete Cosine Transform (DCT) functions, each layer of of PCANet and DCTNet is ess...

LFM signals are widely used in the fields of radar and communication etc., which make signals detection and parameters estimation a very important technology in multicomponent LFM signals. To solve the problems of error detection caused by the cross-terms in WVD-Hough methods and other modified WVD distribution methods, and low parameter estimation precision due to poor timefrequency concentrat...

Abstract Fast (sub-second) spectroscopy with high spectral resolution is of vital importance for revealing quantum chemistry kinetics complex chemical and biological reactions. Fourier transform (FT) spectrometers can achieve operate at hundreds ms time scales in rapid-scan mode. However, the linear translation a scanning mirror imposes stringent time-resolution limitations to these systems, wh...

Time-frequency transforms represent a signal as a mixture of its time domain representation and its frequency domain representation. We present efficient algorithms for the quantum Zak transform and quantum Weyl-Heisenberg transform.

OBJECTIVES This review outlines the methodological fundamentals of the most frequently used non-parametric time-frequency analysis techniques in biomedicine and their main properties, as well as providing decision aids concerning their applications. METHODS The short-term Fourier transform (STFT), the Gabor transform (GT), the S-transform (ST), the continuous Morlet wavelet transform (CMWT), ...

EEG is widely used to record the electrical activity of the brain for detecting various kinds of diseases and disorders of the human brain. EEG signals are contaminated with several unwanted artifacts during EEG recording and these artifacts make the analysis of EEG signal difficult by hiding some valuable information. Time-frequency representation of electroencephalogram (EEG) signal provides ...

Objectives: This review outlines the method ological fundamentals of the most frequently used non-parametric time-frequency analysis techniques in biomedicine and their main properties, as well as providing decision aids concerning their applications. Methods: The short-term Fourier transform (STFT), the Gabor transform (GT), the S-transform (ST), the continuous Morlet wavelet transform (CMWT),...

In the next two lectures, we will continue to expand our toolbox for computing in frequency domain, by adding two important computational tools. The first, the Fast Fourier Transform (FFT) is a family of algorithms for efficiently computing the Discrete Fourier Transform. These algorithms are of great practical importance, as theymake it possible to perform frequency domain analysis of very lar...

0018-9251/03/$17.00 @ 2003 IEEE Two-way antenna radiation pattern at frequency w + wc, Slow-time Doppler two-way antenna radiation pattern Pulse bandwidth Speed of light Covariance of w(k,,t) at time t Cross-range aperture length Energy of RJt) Energy of p( t ) Point target refectivity Fourier transform operator Inverse Fourier transform operator Fourier transform of electric field in antenna a...

Filter banks with fixed time-frequency resolution, such as the Short-Time Fourier Transform (STFT), are a common tool for many audio analysis and processing applications allowing effective implementation via the Fast Fourier Transform (FFT). The fixed time-frequency resolution of the STFT can lead to the undesirable smearing of events in both time and frequency. In this paper, we suggest adapti...