Time-Frequency Signal Analysis and Adaptive Instantaneous Frequency Estimation

Abdoush, Yazan (2019) Time-Frequency Signal Analysis and Adaptive Instantaneous Frequency Estimation, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Ingegneria elettronica, telecomunicazioni e tecnologie dell'informazione, 31 Ciclo.
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Most of the human-made and physical signals have nonstationary spectra that evolve rapidly with time. To study and characterize such signals, the classic time-domain and frequency-domain representations are inadequate, since they do not provide joint time and frequency information; meaning that, they are signal representations in which the time and frequency variables are mutually exclusive. Time-frequency (TF) signal analysis (TFSA) concerns the processing of signals with time-varying spectral content. It allows for the construction of a signal representation in which the time and frequency variables are not averaged with respect to each other, but rather present together. This doctoral thesis has two main points of focus: TFSA based on a linear TF transform with progressive frequency-dependent resolution in the TF domain, known in the literature as the S-transform (ST), and designing adaptive methods for instantaneous frequency (IF) estimation, which is a fundamental concept in TFSA with numerous practical applications. The main original contributions are: 1- Modifications in the existing discrete definitions for implementing and inverting the ST to ensure exact invertibility and eliminate artifacts in the synthesized signal. 2- Derivation of an algorithm for least-squares signal synthesis form a modified discrete ST. 3- Formulation of a computationally efficient, fully discrete, and exactly invertible ST with a controllable TF sampling scheme, providing frequency resolution that can be varied and made as high as required. 4- Accuracy analysis of IF estimation based on a family of linear TF transforms that use Gaussian observation windows to localize the Fourier oscillatory kernel with arbitrarily defined standard deviations, and derivation of closed-form easily interpreted expressions for the bias and the variance of the estimation error. 5- Design of adaptive methods for IF estimation based on linear and quadratic TF representations.

Tipologia del documento
Tesi di dottorato
Abdoush, Yazan
Dottorato di ricerca
Settore disciplinare
Settore concorsuale
Parole chiave
nonstationary signals, short-time Fourier transform, S-transform, wavelet transform, Wigner distribution, instantaneous frequency estimation, time-frequency representation, time-frequency analysis, adaptive estimation.
Data di discussione
8 Aprile 2019

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