Lorentzian Based Adaptive Filters for Impulsive Noise Environments
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Circuits and Systems I: Regular Papers"
DOI: 10.1109/tcsi.2017.2667705
Abstract: In this paper, three Lorentzian based robust adaptive algorithms are proposed for identifying systems in presence of impulsive noise. The first algorithm called Lorentzian adaptive filtering (LAF) is derived from a sliding window type cost… read more here.
Keywords: lorentzian based; hard thresholding; algorithm called; impulsive noise ... See more keywords
Performance Analysis and Architecture of a Clustering Hybrid Algorithm Called FA+GA-DBSCAN Using Artificial Datasets
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DOI: 10.3390/e24070875
Abstract: Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a widely used algorithm for exploratory clustering applications. Despite the DBSCAN algorithm being considered an unsupervised pattern recognition method, it has two parameters that must be… read more here.
Keywords: algorithm called; performance; called dbscan; algorithm ... See more keywords