Trend Analysis of Modal Identification based Real-time Power System Oscillations using L1 Trend Filtering
نویسندگان
چکیده
منابع مشابه
l1 Trend Filtering
The problem of estimating underlying trends in time series data arises in a variety of disciplines. In this paper we propose a variation on Hodrick-Prescott (H-P) filtering, a widely used method for trend estimation. The proposed l1 trend filtering method substitutes a sum of absolute values (i.e., an l1-norm) for the sum of squares used in H-P filtering to penalize variations in the estimated ...
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The problem of estimating underlying trends in time series data arises in a variety of disciplines. In this paper we propose a variation on Hodrick–Prescott (H-P) filtering, a widely used method for trend estimation. The proposed !1 trend filtering method substitutes a sum of absolute values (i.e., !1 norm) for the sum of squares used in H-P filtering to penalize variations in the estimated tre...
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Yu-Xiang Wang1,2 [email protected] James Sharpnack3 [email protected] Alexander J. Smola1,4 [email protected] Ryan J. Tibshirani1,2 [email protected] 1 Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213 2 Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213 3 Mathematics Department, University of California at San Diego, La Jolla, CA 10280 ...
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Streaming applications from algorithmic trading to tra c management deploy Kleene patterns to detect and aggregate arbitrarily-long event sequences, called event trends. State-of-the-art systems process such queries in two steps. Namely, they first construct all trends and then aggregate them. Due to the exponential costs of trend construction, this two-step approach su↵ers from both a long del...
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ژورنال
عنوان ژورنال: International Journal of Robotics and Control Systems
سال: 2021
ISSN: 2775-2658
DOI: 10.31763/ijrcs.v1i2.311