نتایج جستجو برای: time frequency

تعداد نتایج: 2263081  

1998
Mark Coates Ercan Kuruoglu

The overriding aim of this thesis is to investigate the bene ts of focusing time-frequency analysis on particular regions of the time-frequency plane. The thesis examines aspects of such a regionalisation in the analysis of both deterministic signals and stochastic processes. The majority of deterministic energetic time-frequency representations are nonparametric, indicating the distribution of...

Journal: :Proceedings of the National Academy of Sciences of the United States of America 2006
Timothy J Gardner Marcelo O Magnasco

Auditory neurons preserve exquisite temporal information about sound features, but we do not know how the brain uses this information to process the rapidly changing sounds of the natural world. Simple arguments for effective use of temporal information led us to consider the reassignment class of time-frequency representations as a model of auditory processing. Reassigned time-frequency repres...

1996
Metin Bayram Richard G. Baraniuk

We propose a robust method for estimating the time-varying spectrum of a non-stationary random process. Our approach extends Thomson's powerful multiple window spectrum estimation scheme to the time-frequency and timescale planes. The method reenes previous extensions of Thomson's method through optimally concentrated window and wavelet functions and a statistical test for extracting chirping l...

2007
H. Bölcskei R. W. Heath A. J. Paulraj G. B. Giannakis K. J. R. Liu J. K. Cavers B. Yang K. Ben Letaief R. Cheng I. Kang M. P. Fitz S. B. Gelfand M. C. Vanderveen Y. Li L. J. Cimini O. Edfors M. Sandell J. van de Beek K. S. Wilson M. K. Tsatsanis

Over the last decade, the theory of reproducing kernels has made a major breakthrough in the field of pattern recognition. It has led to new algorithms, with improved performance and lower computational cost, for nonlinear analysis in high dimensional feature spaces. Our paper is a further contribution which extends the framework of the so-called kernel learning machines to time-frequency analy...

Journal: :journal of ai and data mining 2014
milad azarbad hamed azami saeid sanei a ebrahimzadeh

the record of human brain neural activities, namely electroencephalogram (eeg), is generally known as a non-stationary and nonlinear signal. in many applications, it is useful to divide the eegs into segments within which the signals can be considered stationary. combination of empirical mode decomposition (emd) and hilbert transform, called hilbert-huang transform (hht), is a new and powerful ...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه تربیت مدرس 1387

چکیده ندارد.

Journal: :Signal Processing 2011
Irena Orovic Srdjan Stankovic Moeness G. Amin

We introduce a new and simple technique for human gait classification based on the time-frequency analysis of radar data. The focus is on the classification of arm movements to discern free vs. confined arm swinging motion. The latter may arise in hostage situation or may be indicative to carrying objects with one or both hands. The motion signatures corresponding to the arm and leg movements a...

Journal: :فیزیک زمین و فضا 0
محمد صادق پرکان دانشجوی کارشناسی ارشد مؤسسة ژئوفیزیک دانشگاه تهران حمیدرضا سیاه کوهی استاد، گروه فیزیک زمین، موسسه زئوفیزیک دانشگاه تهران، ایران علی غلامی دانشیر، گروه فیزیک زمین، موسسه ژئوفیزیک دانشگاه تهارن، ایران

in this paper some new applications of empirical mode decomposition (emd) and hilbert spectrum in seismic ground-roll attenuation, random noise attenuation and spectral decomposition are introduced. hilbert spectrum is a time-frequency representation for hilbert-huang transform which is obtained by combination of instantaneous frequency (if) concept and intrinsic mode function of empirical mode...

2003
Victor Sucic Boualem Boashash

The difficulty of selecting the optimal time-frequency distribution (TFD) for a given real-life signal has been one of the major limiting factors to a wider use of time-frequency analysis tools in practice. This paper, by extending our earlier works on the objective assessment of the performance of TFDs, presents a novel automatic approach for selecting a real-life signal best-performing time-f...

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