A comparison of block based Kalman filter and H-infinity algorithms for blind image separation

DOI10.1007/s10598-021-09535-wzbMath1487.94043OpenAlexW4200139248WikidataQ114226989 ScholiaQ114226989MaRDI QIDQ2135319

P. A. Dinesh, M. Jyothirmayi, S. Sethu Selvi

Publication date: 6 May 2022

Published in: Computational Mathematics and Modeling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10598-021-09535-w

zbMATH Keywords

Kalman filtersparsenessperformance metricsblind image separationH-infinity filter

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Filtering in stochastic control theory (93E11) Computing methodologies for image processing (68U10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Cites Work

• Blind separation of sources. I: An adaptive algorithm based on neuromimetic architecture
• The nonlinear PCA criterion in blind source separation: Relations with other approaches
• Blind Source Separation by Sparse Decomposition in a Signal Dictionary
• Stable recovery of sparse overcomplete representations in the presence of noise

This page was built for publication: A comparison of block based Kalman filter and H-infinity algorithms for blind image separation