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THE LINEAR TIME FREQUENCY ANALYSIS TOOLBOX
International Journal of Wavelets, Multiresolution and Information Processing, 2012The Linear Time Frequency Analysis Toolbox is a MATLAB/Octave toolbox for computational time-frequency analysis. It is intended both as an educational and computational tool. The toolbox provides the basic Gabor, Wilson and MDCT transform along with routines for constructing windows (filter prototypes) and routines for manipulating coefficients.
Peter L. Søndergaard +2 more
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ECG analysis in the Time-Frequency domain
2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE), 2012The Electrocardiogram (ECG) has been established as a powerful diagnostic tool in medicine which provides important information about the patient's heart condition. The correct identification of the QRS complexes is a fundamental step in every automated or semi-automated ECG analysis method.
Neophytou, N. +5 more
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The statistics of time–frequency analysis
Journal of the Franklin Institute, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Time-Frequency Analysis of Musical Instruments
SIAM Review, 2002Summary: This paper describes several approaches to analyzing the frequency, or pitch, content of the sounds produced by musical instruments. The classic method, using Fourier analysis, identifies fundamentals and overtones of individual notes. A second method, using spectrograms, analyzes the changes in fundamentals and overtones over time as several ...
Jeremy F. Alm, James S. Walker
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Evolutionary time-frequency analysis
Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512), 2002Adapted waveform analysis uses libraries of bases and an efficient functional to match a basis to a given signal or family of signals. In particular, wavelet packets and localized trigonometric functions support the expansion of waveforms in bases whose elements have good time-frequency localization properties.
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Parallel time-frequency analysis
International Conference on Acoustics, Speech, and Signal Processing, 2003Conventional time-frequency analysis methods are generally too computationally intensive for real-time implementation. A relatively new method based on a dynamic state-space model is inherently a real-time method and can be implemented in parallel processing.
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2003
Conventionally, time series have been studied either in the time domain or the frequency domain. The representation of a signal in the time domain is localized in time, i.e. the value of the signal at each instant in time is well defined. However, the time representation of a signal is poorly localized in frequency, i.e.
A. Ramachandra Rao +2 more
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Conventionally, time series have been studied either in the time domain or the frequency domain. The representation of a signal in the time domain is localized in time, i.e. the value of the signal at each instant in time is well defined. However, the time representation of a signal is poorly localized in frequency, i.e.
A. Ramachandra Rao +2 more
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Time–Frequency Analysis of the Impulse Response
IEEE Transactions on Signal Processing, 2019The impulse response is a key function for the analysis and design of systems, therefore understanding its properties is a fundamental problem. To investigate the nonstationary structure of the impulse response, we derive its time–frequency representation both in the Wigner and smoothed Wigner distribution domains.
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Time-frequency analysis of musical signals
Proceedings of the IEEE, 1996The major time and frequency analysis methods that have been applied to music processing are traced and application areas described. Techniques are examined in the context of Cohen's class, facilitating comparison and the design of new approaches. A trumpet example illustrates most techniques.
William J. Pielemeier +2 more
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2012
In the previous chapter, we mentioned that one of the main limitations of the Fourier transform is that it does not have time resolution. For calculating the Fourier transform, we assume that the signal is stationary and, consequently, that the activity at different frequencies is constant throughout the whole signal.
Walter J. Freeman, Rodrigo Quian Quiroga
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In the previous chapter, we mentioned that one of the main limitations of the Fourier transform is that it does not have time resolution. For calculating the Fourier transform, we assume that the signal is stationary and, consequently, that the activity at different frequencies is constant throughout the whole signal.
Walter J. Freeman, Rodrigo Quian Quiroga
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