H. Li, P. Stoica, and J. Li. Computationally efficient maximum likelihood estimation of structured covariance matrices. IEEE Trans. Signal Processing, 47(5):1314 -- 1323, May 1999. An Improved Blind Adaptive MMSE Receiver 27 Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
An Improved Blind Adaptive MMSE Receiver for Fast Fading.. - Chen, Mitra (Correct)
....its performance by exploiting the nature of the DS CDMA signal. The typical sample correlation matrix estimate is an unstructured estimator. Clearly, structured correlation matrix estimates may result in better performance if knowledge of properties of the desired correlation matrix is exploited [2, 11]. An asymptotic maximum likelihood (AML) estimate of the structured correlation matrix is presented in [11] which yields a closed form solution for Hermitian Toeplitz correlation matrix estimations. However, in our particular case, the correlation matrix R does not exhibit a Toeplitz structure. ....
....is an unstructured estimator. Clearly, structured correlation matrix estimates may result in better performance if knowledge of properties of the desired correlation matrix is exploited [2, 11] An asymptotic maximum likelihood (AML) estimate of the structured correlation matrix is presented in [11], which yields a closed form solution for Hermitian Toeplitz correlation matrix estimations. However, in our particular case, the correlation matrix R does not exhibit a Toeplitz structure. The importance of a good estimate of R is clearly seen in [4] where suboptimal channel estimators are ....
H. Li, P. Stoica, and J. Li. Computationally efficient maximum likelihood estimation of structured covariance matrices. IEEE Trans. Signal Processing, 47(5):1314 -- 1323, May 1999. An Improved Blind Adaptive MMSE Receiver 27
Computationally Efficient Parameter Estimation for Harmonic.. - Hongbin Li Petre Self-citation (Li Stoica) (Correct)
....for implementing (11) Specifically, it can be shown that the calculation of S T WS, which will become quite time consuming if implemented in a direct manner and when K is large, will reduce to only a few additions provided that the sparsity of S is properly exploited. We refer the readers to [15], where an efficient implementation of an algorithm similar to (11) was discussed in detail. 3 Cram er Rao Bound An asymptotic (for large N) CRB for the case of real valued harmonic sinusoidal signals was derived in [4] In the following, we derive the exact CRB for the parameter estimation ....
H. Li, P. Stoica, and J. Li, "Computationally efficient maximum likelihood estimation of structured covariance matrices," IEEE Transactions on Signal Processing, vol. 47, pp. 1314--1323, May 1999. 14 -0.5-0.4-0.3-0.2-0.1 0 0.1 0.2 0.3 0.4 0.5
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC