Whatever the application domains, when dealing with strongly nonstationary and nonlinear signals, Fourier-based methods and even classical time-frequency methods are no longer able to estimate and track the instantaneous amplitudes and frequencies of each signal component. One possibility to get away from the Heisenberg incertitude constraint is to set a model, which has to be as general as possible in order to be valid in many domains. In that context, we have proposed and studied a new model, which writes as a time-varying polynomial-amplitude and polynomial-phase signal. Parameter estimation is casting as the maximisation of the likelihood function, which is overcome by meta-heuristic approaches, such as simulating annealing. In that pap...
The estimation and analysis of signals that have polynomial phase and constant or time-varying ampli...
International audiencePolynomial phase signals belong to a wide class of nonstationary signals used ...
The broad-based goal of this thesis is to understand, detect, identify and quantify the abstract ent...
International audienceWhatever the application domains, when dealing with strongly nonstationary and...
International audienceWe consider the modeling of non-stationary discrete signals whose amplitude an...
National audienceIn this paper, we consider nonstationary signals with nonlinear amplitude and frequ...
International audienceWe propose an original strategy for estimating and reconstructing mono-compone...
This paper introduces some tools to characterize the phase behav-ior of non stationary signals. Star...
Abstract: Advanced signal processing methods are helpful in the context of diagnostic and fault dete...
International audienceThis paper concerns the parameter estimation of multicomponent damped oscillat...
International audienceAdvanced signal processing methods are helpful in the context of diagnostic an...
International audienceParameter estimation for closely spaced or crossing frequency trajectories is ...
We model non stationary signals by assuming that the phase and the amplitude are both a polynomial f...
This work concentrates on the estimation and reconstruction of highly non-stationary signals having ...
International audienceThe modelling of signal in the context of multiple components, few samples, st...
The estimation and analysis of signals that have polynomial phase and constant or time-varying ampli...
International audiencePolynomial phase signals belong to a wide class of nonstationary signals used ...
The broad-based goal of this thesis is to understand, detect, identify and quantify the abstract ent...
International audienceWhatever the application domains, when dealing with strongly nonstationary and...
International audienceWe consider the modeling of non-stationary discrete signals whose amplitude an...
National audienceIn this paper, we consider nonstationary signals with nonlinear amplitude and frequ...
International audienceWe propose an original strategy for estimating and reconstructing mono-compone...
This paper introduces some tools to characterize the phase behav-ior of non stationary signals. Star...
Abstract: Advanced signal processing methods are helpful in the context of diagnostic and fault dete...
International audienceThis paper concerns the parameter estimation of multicomponent damped oscillat...
International audienceAdvanced signal processing methods are helpful in the context of diagnostic an...
International audienceParameter estimation for closely spaced or crossing frequency trajectories is ...
We model non stationary signals by assuming that the phase and the amplitude are both a polynomial f...
This work concentrates on the estimation and reconstruction of highly non-stationary signals having ...
International audienceThe modelling of signal in the context of multiple components, few samples, st...
The estimation and analysis of signals that have polynomial phase and constant or time-varying ampli...
International audiencePolynomial phase signals belong to a wide class of nonstationary signals used ...
The broad-based goal of this thesis is to understand, detect, identify and quantify the abstract ent...