Newtonized Orthogonal Matching Pursuit: Frequency Estimation Over the Continuum
نویسندگان
چکیده
منابع مشابه
Newtonized Orthogonal Matching Pursuit for Line Spectrum Estimation with Multiple Measurement Vectors
A Newtonized orthogonal matching pursuit (NOMP) algorithm is proposed to estimate continuous frequencies and amplitudes of a mixture of sinusoids with multiple measurement vectors (MMVs). The proposed algorithm includes two key steps: Detecting a new sinusoid on an oversampled discrete Fourier transform (DFT) grid and refining the parameters of already detected sinusoids to avoid the problem of...
متن کاملDirection of arrival estimation using modified orthogonal matching pursuit algorithm
Direction of arrival (DOA) estimation is a sparse reconstruction problem. However, conventional orthogonal matching pursuit (OMP) may fail to identify the correct atoms since the redundant dictionary composed of the direction vectors is highly coherent. To mitigate the coherence problem, in this paper, we propose a modified OMP by constructing data dependent sensing dictionary for sparse recons...
متن کاملMultichannel Image Estimation via Simultaneous Orthogonal Matching Pursuit
In modern imaging systems, it is possible to collect information about an image on multiple channels. The simplest example is that of a color image which consists of three channels (i.e. red, green, and blue). However, there are more complicated situations such as those that arise in hyperspectral imaging. Furthermore, most of these images are sparse or highly compressible. We need not measure ...
متن کاملTuning Free Orthogonal Matching Pursuit
Orthogonal matching pursuit (OMP) is a widely used compressive sensing (CS) algorithm for recovering sparse signals in noisy linear regression models. The performance of OMP depends on its stopping criteria (SC). SC for OMP discussed in literature typically assumes knowledge of either the sparsity of the signal to be estimated k0 or noise variance σ , both of which are unavailable in many pract...
متن کاملOrthogonal Matching Pursuit with Replacement
In this paper, we consider the problem of compressed sensing where the goal is to recover all sparsevectors using a small number of fixed linear measurements. For this problem, we propose a novelpartial hard-thresholding operator that leads to a general family of iterative algorithms. While oneextreme of the family yields well known hard thresholding algorithms like ITI and HTP[17, ...
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: IEEE Transactions on Signal Processing
سال: 2016
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2016.2580523