Sparse Andrew's Sine Norm Promoting Adaptive Algorithm under Non-Gaussian Noises
Abdul Hadi, Xinqi Huang, Burhan Ali, Yingsong Li
20222022 IEEE 5th International Conference on Electronic Information and Communication Technology (ICEICT)12 citationsDOI
Abstract
Two sparse adaptive filtering (AF) algorithms based on Andrew's sine estimator (ASE) are presented to achieve improved performance for identifying sparse systems, where the ASE is derived within the least-square framework. Furthermore, zero-attracting (ZA) scheme is used in ASE to construct ZA-ASE and its re-weighting form (RZA-ASE) to combat non-Gaussian noises and use the sparse characteristics of the system. Their performance is investigated via simulations and compared with the least-mean square (LMS) and the maximum correntropy criterion (MCC) algorithms to show their superior performance.
Topics & Concepts
AlgorithmWeightingGaussianEstimatorComputer scienceNorm (philosophy)Least mean squares filterAdaptive filterMathematicsStatisticsPhysicsLawPolitical scienceAcousticsQuantum mechanicsAdvanced Adaptive Filtering TechniquesBlind Source Separation TechniquesStructural Health Monitoring Techniques