Fourier methods are fundamental tools to analyze random fields. Statistical structures of homogeneous Gaussian random fields are completely characterized by the power spectrum. In non-Gaussian random fields, polyspectra, higher-order counterparts of the power spectrum, are usually considered to characterize statistical information contained in the fields. However, it is not trivial how the Four...

Despite the complexity and diversity of natural scenes, humans are very fast and accurate at identifying basic-level scene categories. In this paper we develop a new technique (based on Bubbles, Gosselin & Schyns, 2001a; Schyns, Bonnar, & Gosselin, 2002) to determine some of the information requirements of basic-level scene categorizations. Using 2400 scenes from an established scene database (...

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...

In Fourier spectroscopy, the absorption mode spectrum V(f) and the dispersion mode spectrum U(f) are computed from the experimentally measured impulse response /z(t). Clearly, this general principle must be applicable here as well. Some consequences of practical importance will be discussed in this paper. In practical Fourier spectroscopy a periodic pulse sequence is used to excite the spin sys...

We present several observations on a novel method for the evaluation of the internal loss properties in semiconductor lasers. The method we use involves Fourier analysis of the Fabry–Perot mode spectrum when operating the device below lasing threshold. The observation of various structural features in the Fourier transform domain allows us to extract important information on the laser cavity. A...

People can recognize the meaning or gist of a scene from a single glance, and a few recent studies have begun to examine the sorts of information that contribute to scene gist recognition. The authors of the present study used visual masking coupled with image manipulations (randomizing phase while maintaining the Fourier amplitude spectrum; random image structure evolution [RISE]; J. Sadr & P....

Parametric enhancement of the appearance probability of the neutrino oscillation under the inhomogeneous matter is studied. Fourier expansion of the matter density profile leads to a simple resonance condition and manifests that each Fourier mode modifies the energy spectrum of oscillation probability at around the corresponding energy; below the MSW resonance energy, a large-scale variation mo...

This paper presents a novel method for classifying an image into one of predeened classes in a data bank by applying mutual information to a representation of the Fourier amplitude domain. Template and test images are made translation and rotation invariant through the Fourier-Mellin transform. While mutual information could be employed here, we choose instead to apply it to the lower dimension...

In this paper, our aim is to derive a phase spectrum representation computed via the short-time Fourier transform. Specifically, we are interested in developing a narrow-band speech representation – employing 20-40 ms analysis windows. Furthermore, this representation should be as physically meaningful as the magnitude spectrum. To achieve these ends, we concentrate on instantaneous frequency (...

We discuss how an inner-shell electron energy-loss spectrum can be processed using Bayesian (maximum-entropy or maximum-likelihood) deconvolution to simultaneously remove plural scattering and improve the energy resolution. As in Fourier-ratio deconvolution, a low-loss spectrum (recorded from the same area of specimen) is used as a kernel or resolution function. This procedure avoids the need t...