Power System State Estimation via Feasible Point Pursuit: Algorithms and Cramér-Rao Bound
نویسندگان
چکیده
منابع مشابه
Phase Retrieval Using Feasible Point Pursuit: Algorithms and Cramér-Rao Bound
Reconstructing a signal from squared linear (rankone quadratic) measurements is a challenging problem with important applications in optics and imaging, where it is known as phase retrieval. This paper proposes two new phase retrieval algorithms based on non-convex quadratically constrained quadratic programming (QCQP) formulations, and a recently proposed approximation technique dubbed feasibl...
متن کاملCramér-Rao bound for range estimation
In this paper, we derive the Cramér-Rao bound (CRB) for range estimation, which does not only exploit the range information in the time delay, but also in the amplitude of the received signal. This new bound is lower than the conventional CRB that only makes use of the range information in the time delay. We investigate the new bound in an additive white Gaussian noise (AWGN) channel with atten...
متن کاملUniformly Improving the Cramér-Rao Bound and Maximum-Likelihood Estimation
An important aspect of estimation theory is characterizing the best achievable performance in a given estimation problem, as well as determining estimators that achieve the optimal performance. The traditional Cramér-Rao type bounds provide benchmarks on the variance of any estimator of a deterministic parameter vector under suitable regularity conditions, while requiring a-priori specification...
متن کاملA constrained hybrid Cramér-Rao bound for parameter estimation
In statistical signal processing, hybrid parameter estimation refers to the case where the parameters vector to estimate contains both non-random and random parameters. Numerous works have shown the versatility of deterministic constrained Cramér-Rao bound for estimation performance analysis and design of a system of measurement. However in many systems both random and non-random parameters may...
متن کاملThe Cramér-Rao bound for estimation-after-selection
In many practical parameter estimation problems, a model selection is made prior to estimation. In this paper, we consider the problem of estimating an unknown parameter of a selected population, where the population is chosen from a population set by using a predetermined selection rule. Since the selection step may have an important impact on subsequent estimation, ignoring it could lead to b...
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: 2018
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2018.2791977