A new stochastic algorithm inspired on genetic algorithms to estimate signals with finite rate of innovation from noisy samples

DOI10.1016/j.sigpro.2009.05.022zbMath1177.94010OpenAlexW2071317135MaRDI QIDQ1048784

Pedro M. Crespo, Aitor Erdozain

Publication date: 8 January 2010

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2009.05.022

zbMATH Keywords

genetic algorithmsGibbs samplingsignals with finite rate of innovation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Software, source code, etc. for problems pertaining to information and communication theory (94-04)

Related Items (1)

Reconstruction of aperiodic FRI signals and estimation of the rate of innovation based on the state space method

Cites Work

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• Estimating Signals With Finite Rate of Innovation From Noisy Samples: A Stochastic Algorithm
• Sampling signals with finite rate of innovation
• Sampling and reconstruction of signals with finite rate of innovation in the presence of noise

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