Add to ORKGInternational audienceWe develop a parametric high-resolution method for the estimation of the frequency nodes of linear combinations of complex exponentials with exponential damping. We use Kronecker’s theorem to formulate the associated nonlinear least squares problem as an optimization problem in the space of vectors generating Hankel matrices of fixed rank. Approximate solutions to this problem are obtained by using the alternating direction method of multipliers. Finally, we extract the frequency estimates from the con-eigenvectors of the solution Hankel matrix. The resulting algorithm is simple, easy to implement and can be applied to data with equally spaced samples with approximation weights, which for instance allows cases of missi...
In this paper we propose a new matrix pencil based method for estimating parameters (frequencies and...
Periodic signals are encountered in many applications. Such signals can be modelled by a weighted su...
noAbstract: We develop a novel approach to estimate the n unknown constituent frequencies of a sinu...
International audienceWe develop a parametric high-resolution method for the estimation of the frequ...
We develop a parametric high-resolution method for the estimation of the frequency nodes of linear c...
Spectral estimation is an important classical problem that has received considerable attention in th...
We develop fixed-point algorithms for the approximation of structured matrices with rank penalties. ...
We introduce a flexible optimization framework for nuclear norm minimization of matrices with linear...
For noiseless sampled data, we describe the close connections between Prony--like methods, namely th...
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer En...
This paper considers parameter estimation of superimposed exponential signals in multiplicative and ...
The parameter estimation of damped sinusoidal signals is an important issue in spectral analysis and...
International audienceWe study the decomposition of a multivariate Hankel matrix H_σ as a sum of Han...
For detection and estimation of 2-D frequencies from a 2-D array of data using a subspace decomposit...
An efficient computational algorithm is proposed for estimating the parameters of undamped exponenti...
In this paper we propose a new matrix pencil based method for estimating parameters (frequencies and...
Periodic signals are encountered in many applications. Such signals can be modelled by a weighted su...
noAbstract: We develop a novel approach to estimate the n unknown constituent frequencies of a sinu...
International audienceWe develop a parametric high-resolution method for the estimation of the frequ...
We develop a parametric high-resolution method for the estimation of the frequency nodes of linear c...
Spectral estimation is an important classical problem that has received considerable attention in th...
We develop fixed-point algorithms for the approximation of structured matrices with rank penalties. ...
We introduce a flexible optimization framework for nuclear norm minimization of matrices with linear...
For noiseless sampled data, we describe the close connections between Prony--like methods, namely th...
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer En...
This paper considers parameter estimation of superimposed exponential signals in multiplicative and ...
The parameter estimation of damped sinusoidal signals is an important issue in spectral analysis and...
International audienceWe study the decomposition of a multivariate Hankel matrix H_σ as a sum of Han...
For detection and estimation of 2-D frequencies from a 2-D array of data using a subspace decomposit...
An efficient computational algorithm is proposed for estimating the parameters of undamped exponenti...
In this paper we propose a new matrix pencil based method for estimating parameters (frequencies and...
Periodic signals are encountered in many applications. Such signals can be modelled by a weighted su...
noAbstract: We develop a novel approach to estimate the n unknown constituent frequencies of a sinu...