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Spectral Analysis

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Spectral Analysis
Publications: 20,868| Citation Count: 109,707
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    • Spectral analysis is an important signal processing tool for seismic data. The transformation of a seismogram into the frequency domain is the basis for a significant number of processing algorithms and interpretive methods...

    Avijit Chakrabortyet al. Frequency-time decomposition of seismic data using wavelet-based metho...

    • Spectral analysis is a useful tool in engineering applications but many practical problems are encountered in computing power spectral densities (PSD), particularly in laser Doppler velocimetry where data are irregularly sampled. Methods to compute PSD are usely based on discrete Fourier transforms such as FFT. A non linear spectral analysis approach is tested and found to give better results, particularly with short data records. Results are also quite promising when non linear spectral analysis is combined with signal reconstruction to process irregularly sampled data...

    D. Veynanteet al. Application of nonlinear spectral analysis and signal reconstruction t...

    • Spectral analysis is a particularly valuable method for seeking dependences expressed as lags between different magnitudes. Its use in this article was first determined by the search for maximum objectivity in the observation of time series. The possibility of applying it to a large number of series was then examined. This twin requirement resulted from a desire to avoid the criticism generally levelled at statistical studies concerning cyclical movements of the economy. Spectral analysis is based on the theory of stochastic processes...

    Claude Dieboltet al. New international evidence on the cyclical behaviour of output: Kuznet...

    • Spectral analysis is a recently proposed method for feature extraction. Studies show that the features extracted by spectral analysis can also be used to classification...

    Ruicong Zhiet al. Discriminant spectral analysis for facial expression recognition

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