Robust detection of monontonic trend of a data sequence in the presence of impulsive noise
نویسندگان
چکیده
Robust detection of monotonic trend of a data sequence, when the data is subject to gross errors, is investigated. The method involves detection of the outliers by using the statistics of the available data and eliminating or estimating them for better line fitting where the slope of the fitted line indicates the trend of the sequence. Examples demonstrate the performance of the method via Monte Carlo simulations.
منابع مشابه
A 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 کاملA Novel Method for Detection of Epilepsy in Short and Noisy EEG Signals Using Ordinal Pattern Analysis
Introduction: In this paper, a novel complexity measure is proposed to detect dynamical changes in nonlinear systems using ordinal pattern analysis of time series data taken from the system. Epilepsy is considered as a dynamical change in nonlinear and complex brain system. The ability of the proposed measure for characterizing the normal and epileptic EEG signals when the signal is short or is...
متن کاملAdaptive-Filtering-Based Algorithm for Impulsive Noise Cancellation from ECG Signal
Suppression of noise and artifacts is a necessary step in biomedical data processing. Adaptive filtering is known as useful method to overcome this problem. Among various contaminants, there are some situations such as electrical activities of muscles contribute to impulsive noise. This paper deals with modeling real-life muscle noise with α-stable probability distribution and adaptive filterin...
متن کاملAn Effective Approach for Robust Metric Learning in the Presence of Label Noise
Many algorithms in machine learning, pattern recognition, and data mining are based on a similarity/distance measure. For example, the kNN classifier and clustering algorithms such as k-means require a similarity/distance function. Also, in Content-Based Information Retrieval (CBIR) systems, we need to rank the retrieved objects based on the similarity to the query. As generic measures such as ...
متن کاملA Suitable Coding Scheme for Broadband Power-line Communication
This paper introduces three coding strategies for using the Luby Transform (LT) code in a relay aided power-line communication scheme. In the first method, the relay decodes the received packets and re-encodes them for transmission towards the destination. In the second method, the relay only forwardes a random linear combination of its received packets towards the destination, while in the thi...
متن کامل