Analyzing Image Structure by Multidimensional Frequency Modulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new class of multilinear functions for polynomial phase signal analysis
IEEE Transactions on Signal Processing
Long-range channel prediction based on nonstationary parametric modeling
IEEE Transactions on Signal Processing
Multiscale AM-FM demodulation and image reconstruction methods with improved accuracy
IEEE Transactions on Image Processing
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Procedures for selecting the amplitude and phase models of a polynomial phase signal (PPS) modulated by a nonstationary random process are presented. The model selection is performed by using nonlinear least-squares type phase and amplitude parameter estimators with sequential generalizations of the Bonferroni test. Simulation results are used to analyze the performance of the procedures. An application to modeling of real passive acoustic data is presented