\(q\)-state space least mean family of algorithms

DOI10.1007/s00034-017-0569-7zbMath1427.93280OpenAlexW2613924551MaRDI QIDQ2003218

Yanyan Li

Publication date: 16 July 2019

Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00034-017-0569-7

zbMATH Keywords

convergence analysis\(q\)-calculusleast mean square algorithms\(q\)-state space least mean algorithmsmodel-based algorithms

Mathematics Subject Classification ID

Least squares and related methods for stochastic control systems (93E24)

Related Items (5)

Efficient time-varying \(q\)-parameter design for \(q\)-incremental least mean square algorithm with noisy links ⋮ Diffusion quantum-least mean square algorithm with steady-state analysis ⋮ The \(q\)-gradient LMS spline adaptive filtering algorithm and its variable step-size variant ⋮ \(q\)-state space least mean family of algorithms ⋮ A limited memory \(q\)-BFGS algorithm for unconstrained optimization problems

Uses Software

• EnKF

Cites Work

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• Fractional order estimation schemes for fractional and integer order systems with constant and variable fractional order colored noise
• Dual estimation of fractional variable order based on the unscented fractional order Kalman filter for direct and networked measurements
• A note on the \(q\)-derivative operator
• Lattice PFBLMS: Fast covering structure for efficient implementation of frequency-domain adaptive filters
• \(q\)-state space least mean family of algorithms
• Adaptive Filtering
• The q-Gradient Vector for Unconstrained Continuous Optimization Problems
• Kalman Filtering

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