Fast Randomized Algorithms for Robust Estimation of Location
نویسندگان
چکیده
A fundamental procedure appearing within such clustering methods as k-Means, Expectation Maximization, Fuzzy-C-Means and Minimum Message Length is that of computing estimators of location. Most estimators of location exhibiting useful robustness properties require at least quadratic time to compute, far too slow for large data mining applications. In this paper, we propose O(Dn p n)-time random-ized algorithms for computing robust estimators of location, where n is the size of the data set, and D is the dimension.
منابع مشابه
A Robust Adaptive Observer-Based Time Varying Fault Estimation
This paper presents a new observer design methodology for a time varying actuator fault estimation. A new linear matrix inequality (LMI) design algorithm is developed to tackle the limitations (e.g. equality constraint and robustness problems) of the well known so called fast adaptive fault estimation observer (FAFE). The FAFE is capable of estimating a wide range of time-varying actuator fault...
متن کاملA Robust Distributed Estimation Algorithm under Alpha-Stable Noise Condition
Robust adaptive estimation of unknown parameter has been an important issue in recent years for reliable operation in the distributed networks. The conventional adaptive estimation algorithms that rely on mean square error (MSE) criterion exhibit good performance in the presence of Gaussian noise, but their performance drastically decreases under impulsive noise. In this paper, we propose a rob...
متن کاملEstimation of LOS Rates for Target Tracking Problems using EKF and UKF Algorithms- a Comparative Study
One of the most important problem in target tracking is Line Of Sight (LOS) rate estimation for using from PN (proportional navigation) guidance law. This paper deals on estimation of position and LOS rates of target with respect to the pursuer from available noisy RF seeker and tracker measurements. Due to many important for exact estimation on tracking problems must target position and Line O...
متن کاملRobust state estimation in power systems using pre-filtering measurement data
State estimation is the foundation of any control and decision making in power networks. The first requirement for a secure network is a precise and safe state estimator in order to make decisions based on accurate knowledge of the network status. This paper introduces a new estimator which is able to detect bad data with few calculations without need for repetitions and estimation residual cal...
متن کاملFast Randomized Algorithms for Convex Optimization and Statistical Estimation
Fast Randomized Algorithms for Convex Optimization and Statistical Estimation
متن کامل