Many natural phenomena, including geologic events and geophysical data, are fundamentally nonstationary exhibiting statistical variation that changes in space and time. Time-frequency characterization is useful for analyzing such data, seismic traces in particular. We present a novel time-frequency decomposition, which aims at depicting the nonstationary character of seismic data. The proposed ...

Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automate...

This paper is concerned with a synthesis study of the fast Fourier transform (FFT), the short time Fourier transform (STFT and the Wigner distribution (WD) in analysing the phonocardiogram signal (PCG) or heart cardiac sounds.     The FFT (Fast Fourier Transform) can provide a basic understanding of the frequency contents of the heart sounds. The STFT is obtained by calculating the Fourier tran...

In audio processing applications, phase retrieval (PR) is often performed from the magnitude of short-time Fourier transform (STFT) coefficients. Although PR performance has been observed to depend on considered STFT parameters and data, extent this dependence not systematically evaluated yet. To address this, we studied three algorithms for various types content such as redundancy, time-freque...

FFT-based nonuniform filter banks are proposed based on channelsized inverse FFTs applied to nonuniform frequency-partitions (or overlap-add decompositions) of the Short Time Fourier Transform (STFT). Audio filter banks (particularly octave filter banks) are considered as application examples. Trade-offs discussed include perfect reconstruction, aliasing cancellation, flexibility of filterchann...

In this paper we will review the pattern recognition by wavelet transform in the way that it is applied in medical diagnosis and we will discuss about the idea of wavelet networks as a classifier of vital signals. For example, this method can be used for resolution of preprocessed signals to determine the people who subject to exacerbation of Ventricular Tachycardia (VT). Keywords-component; wa...

where w(τ) is a real-valued even lag window. Implementations (hardware and software) of this transform are already widely present in practice. The STFT is linear and very simple for realization. However, it has some serious drawbacks. The most important one lies in its low concentration in the TF plane, when highly nonstationary signals are analyzed. In order to improve TF representation, vario...