In this paper, we introduce a novel algorithm to perform multi-scale Fourier transform analysis of piecewise stationary signals with application to automatic speech recognition. Such signals are composed of quasi-stationary segments of variable lengths. Therefore, in the proposed algorithm, signals are analyzed with multiple-sized windows. Resulting power spectra are then normalized such that t...

It is very important to capture distant-talking speech with high quality for teleconferencing systems or voice-controlled systems. For this purpose, microphone array steering and Fourier spectral subtraction, for example, are ideal candidates. A combination technique using both microphone array steering and Fourier spectral subtraction has also been proposed to improve performance. However, it ...

spectral decomposition is a powerful tool for analysis of seismic data. fourier transform determines the frequency contents of a signal. but for analysis of non-stationary signals, 1-d transform to frequency domain is not sufficient. in early years, transforming of seismic traces into time and frequency domain was done via windowed fourier transform, called a short time fourier transform (stft)...

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes a...

The stability of macroeconomic variables and whether the impact a shock on these is permanent or temporary important for policy-makers researchers. As an indicator growth prosperity, gross domestic product (GDP) among variables. After all, due to advantages current panel data analysis techniques over conventional methods, it use aforementioned methods in analyzing existence unit-root GDP. Accor...

Many random phenomena in the environmental and geophysical sciences are functions of both space and time; these are usually called spatio-temporal processes. Typically, the spatio-temporal process is observed over discrete equidistant time and at irregularly spaced locations in space. One important aim is to develop statistical models based on what is observed. While doing so a commonly used as...

To determine whether an industry exhibits constant returns to scale, whether the production fUnction is homothetic, or whether inputs are separabl~ a common approach is to specify a cost function, estimate its parameters using data such as prices and quantities of inputs, and then test the parametric restrictions corresponding to constant returns, a homothetic technology, or separability. Stati...