Multi-innovation stochastic gradient algorithms for dual-rate sampled systems with preload nonlinearity
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Publication:1761579
DOI10.1016/J.AML.2012.04.007zbMath1251.93130OpenAlexW2013480405MaRDI QIDQ1761579
Lixing Lv, Jing Chen, Ruifeng Ding
Publication date: 15 November 2012
Published in: Applied Mathematics Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.aml.2012.04.007
parameter estimationnonlinear systemstochastic gradientmulti-innovation identificationdual-rate system
Sampled-data control/observation systems (93C57) Identification in stochastic control theory (93E12)
Related Items (8)
Several gradient parameter estimation algorithms for dual-rate sampled systems ⋮ A novel two-stage estimation algorithm for nonlinear Hammerstein-Wiener systems from noisy input and output data ⋮ Least squares algorithm for an input nonlinear system with a dynamic subspace state space model ⋮ Newton iterative identification for a class of output nonlinear systems with moving average noises ⋮ Two identification methods for dual-rate sampled-data nonlinear output-error systems ⋮ Identification of dual-rate sampled Hammerstein systems with a piecewise-linear nonlinearity using the key variable separation technique ⋮ Convergence Analysis of Weighted Stochastic Gradient Identification Algorithms Based on Latest‐Estimation for ARX Models ⋮ Stochastic gradient with changing forgetting factor-based parameter identification for Wiener systems
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