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- Zhao Tan, Peng Yang, Arye Nehorai
- IEEE Transactions on Signal Processing
- 2014

In traditional compressed sensing theory, the dictionary matrix is given a priori, whereas in real applications this matrix suffers from random noise and fluctuations. In this paper, we consider a signal model where each column in the dictionary matrix is affected by a structured noise. This formulation is common in direction-of-arrival (DOA) estimation of… (More)

Chronic hepatitis B virus (HBV) carrier status has a critical impact on clinical management of patients with IgA nephropathy (IgAN) who are treated with corticosteroids, because corticosteroids may enhance HBV replication. This study compared corticosteroids and antivirals combined therapy with corticosteroids monotherapy on patients of IgAN who were also… (More)

- Zhao Tan, Yonina C. Eldar, Amir Beck, Arye Nehorai
- IEEE Transactions on Signal Processing
- 2014

We consider algorithms and recovery guarantees for the analysis sparse model in which the signal is sparse with respect to a highly coherent frame. We consider the use of a monotone version of the fast iterative shrinkage-thresholding algorithm (MFISTA) to solve the analysis sparse recovery problem. Since the proximal operator in MFISTA does not have a… (More)

- Zhao Tan, Arye Nehorai
- IEEE Signal Processing Letters
- 2014

In this letter, we consider the problem of direction of arrival estimation using sparsity enforced reconstruction methods. Co-prime arrays with M + N sensors are utilized to increase the degrees of the freedom from O(M + N) to O(MN). The key to the success of sparse-based direction of arrival estimation is that every target must fall on the predefined grid.… (More)

- Zhao Tan, Yonina C. Eldar, Arye Nehorai
- IEEE Transactions on Signal Processing
- 2014

We consider the problem of direction of arrival (DOA) estimation using a recently proposed structure of nonuniform linear arrays, referred to as co-prime arrays. By exploiting the second order statistical information of the received signals, co-prime arrays exhibit O(MN) degrees of freedom with only M+N sensors. A sparsity-based recovery algorithm is… (More)

- Zhao Tan, Peng Yang, Arye Nehorai
- IEEE Trans. Smart Grid
- 2014

—In this paper, we propose a new model of demand response management for the future smart grid that integrates plug-in electric vehicles and renewable distributed generators. A price scheme considering fluctuation cost is developed. We consider a market where users have the flexibility to sell back the energy generated from their distributed generators or… (More)

- Zhao Tan, Peng Yang, Arye Nehorai
- ArXiv
- 2013

In traditional compressed sensing theory, the dictionary matrix is given a priori, whereas in real applications this matrix suffers from random noise and fluctuations. In this paper we consider a signal model where each column in the dictionary matrix is affected by a structured noise. This formulation is common in problems such as radar signal processing… (More)

- Zhao Tan, Peng Yang, Arye Nehorai
- 2013 5th IEEE International Workshop on…
- 2013

In traditional compressed sensing theory, the dictionary matrix is given a priori, while in real applications this matrix suffers from random noise and fluctuations. This paper considers a signal model where each column in the dictionary matrix is affected by a structured noise. This formulation is common in radar related applications and… (More)

- Zhao Tan, Peng Yang, Arye Nehorai
- 2013 5th IEEE International Workshop on…
- 2013

In this paper, we propose a new model of demand response management for the future smart grid that integrates plug-in electric vehicles. A price scheme considering fluctuation cost is developed. We consider a market where users have the flexibility to sell back the energy generated from their distributed generators or the energy stored in their plug-in… (More)

- Zhao Tan, Peng Yang, Arye Nehorai
- 2013 IEEE International Conference on Acoustics…
- 2013

In this paper we propose a sparse model to accurately estimate target locations in a distributed multiple-input multiple-output (MIMO) radar system with phase mismatches at transmitters and receivers. We formulate the localization problem based on maximum a posteriori (MAP) estimation. To reduce the effect of phase mismatches we develop a novel alternating… (More)