Self-tuning filters and predictors for two-dimensional systems Part 1: Algorithms

DOI10.1080/00207178508933375zbMath0596.93058OpenAlexW2047159501WikidataQ126256898 ScholiaQ126256898MaRDI QIDQ3728782

Peter E. Wellstead, J. R. Caldas Pinto

Publication date: 1985

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207178508933375

zbMATH Keywords

maximum likelihood estimatesadaptive algorithmsprediction and filtering two-dimensional processes

Mathematics Subject Classification ID

Related Items (8)

Realization and performance evaluation of a class of image models for recursive restoration problems ⋮ Two-dimensional minimum variance and self-tuning controllers ⋮ Image modeling and restoration: A new approach ⋮ Self-tuning filters and predictors for two-dimensional systems Part 3: Prediction applications ⋮ Self-tuning prediction and control for two-dimensional processes Part 1: Fixed parameter algorithms ⋮ Variance calculations for two-dimensional ARMA processes ⋮ Unnamed Item ⋮ A simple method of recursive parameter identification for a class of distributed parameter systems

Cites Work

• Unnamed Item
• Two-dimensional digital signal processing I. Linear filters
• Estimation and identification of two-dimensional images
• Self-tuning filters and predictors for two-dimensional systems Part 2: Smoothing applications
• A self-tuning predictor
• Kalman filtering in two dimensions
• A self-tuning filter for fixed-lag smoothing
• Dynamic representation and recursive estimation of cyclic and two-dimensional processes

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