A simultaneous sparse approximation method for multidimensional harmonic retrieval
نویسندگان
چکیده
منابع مشابه
A Simultaneous Sparse Approximation Method for Multidimensional Harmonic Retrieval
In this paper, a new method for the estimation of the parameters of multidimensional (R-D) harmonic and damped complex signals in noise is presented. The problem is formulated as R simultaneous sparse approximations of multiple 1-D signals. To get a method able to handle large size signals while maintaining a sufficient resolution, a multigrid dictionary refinement technique is associated to th...
متن کاملFast Algorithms for Multidimensional Harmonic Retrieval
Classic multidimensional harmonic retrieval is the estimation problem in a variety of practical applications, including sensor array processing, radar, mobile communications, multiple-input multiple-output (MIMO) channel estimation and nuclear magnetic resonance spectroscopy. Numerous parametric subspace approaches have been proposed recently to solve this problem, among which the so-called ESP...
متن کاملSimultaneous Sparse Approximation Using an Iterative Method with Adaptive Thresholding
This paper studies the problem of Simultaneous Sparse Approximation (SSA). This problem arises in many applications which work with multiple signals maintaining some degree of dependency such as radar and sensor networks. In this paper, we introduce a new method towards joint recovery of several independent sparse signals with the same support. We provide an analytical discussion on the converg...
متن کاملAlmost sure identifiability of multidimensional harmonic retrieval
Two-dimensional (2-D) and, more generally, multidimensional harmonic retrieval is of interest in a variety of applications, including transmitter localization and joint time and frequency offset estimation in wireless communications. The associated identifiability problem is key in understanding the fundamental limitations of parametric methods in terms of the number of harmonics that can be re...
متن کاملSparse pseudospectral approximation method
Multivariate global polynomial approximations – such as polynomial chaos or stochastic collocation methods – are now in widespread use for sensitivity analysis and uncertainty quantification. The pseudospectral variety of these methods uses a numerical integration rule to approximate the Fourier-type coefficients of a truncated expansion in orthogonal polynomials. For problems in more than two ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Signal Processing
سال: 2017
ISSN: 0165-1684
DOI: 10.1016/j.sigpro.2016.07.029