منابع مشابه
Parameter Estimation for Relational Kalman Filtering
The Kalman Filter (KF) is pervasively used to control a vast array of consumer, health and defense products. By grouping sets of symmetric state variables, the Relational Kalman Filter (RKF) enables to scale the exact KF for large-scale dynamic systems. In this paper, we provide a parameter learning algorithm for RKF, and a regrouping algorithm that prevents the degeneration of the relational s...
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In wireless cellular communications, accurate local mean (shadow) power estimation performed at a mobile station is important for use in power control, handoff, and adaptive transmission. Window-based weighted sample average shadow power estimators are commonly used due to their simplicity. In practice, the performance of these estimators degrades severely when the window size deviates beyond a...
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INTRODUCTION A Kalman filter provides causal operation, which is desirable in several rapid imaging applications. A successful real-time implementation of a Kalman filter has recently been developed used with spiral trajectories for applications in dynamic cardiac MRI and has been shown to outperform an existing sliding window method [1,2]., However there are different ways to estimate paramete...
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MOTIVATION In this paper, we propose using the Kalman filter (KF) as a pre-processing step in microarray-based molecular diagnosis. Incorporating the expression covariance between genes is important in such classification problems, since this represents the functional relationships that govern tissue state. Failing to fulfil such requirements may result in biologically implausible class predict...
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ژورنال
عنوان ژورنال: IEEE Transactions on Aerospace and Electronic Systems
سال: 2006
ISSN: 0018-9251
DOI: 10.1109/taes.2006.1603411