AR-BLS adapts BLS robustness to non-Gaussian noise via an adaptive kernel that includes multiple M-estimators, with alternating optimization, convergence proof, and empirical tests.
Identification of nonlinear dynamic system using a novel recurrent wavelet neural network based on the pipelined architecture,
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Broad learning system with robust adaptive kernel
AR-BLS adapts BLS robustness to non-Gaussian noise via an adaptive kernel that includes multiple M-estimators, with alternating optimization, convergence proof, and empirical tests.