Adaptive signal processing
Adaptive algorithms and stochastic approximations
Adaptive algorithms and stochastic approximations
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Adaptive Filters: Theory and Applications
Adaptive Filters: Theory and Applications
Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability
Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability
An Incremental Gradient(-Projection) Method with Momentum Term and Adaptive Stepsize Rule
SIAM Journal on Optimization
A stochastic gradient adaptive filter with gradient adaptive stepsize
IEEE Transactions on Signal Processing
On the learning mechanism of adaptive filters
IEEE Transactions on Signal Processing
Line search algorithms for adaptive filtering
IEEE Transactions on Signal Processing
A new class of gradient adaptive step-size LMS algorithms
IEEE Transactions on Signal Processing
IEEE Transactions on Education
A geometric approach to the linear modelling
CSS'11 Proceedings of the 5th WSEAS international conference on Circuits, systems and signals
On the convergence of LMS filters under periodic signals
Digital Signal Processing
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The use of the Armijo rule for the automatic selection of the step size within the class of stochastic gradient descent algorithms is investigated, and the Armijo rule learning rate least mean square (ALR-LMS) algorithm is introduced. This algorithm is derived by integrating an appropriately modified version of the Armijo line search to the least mean square filter update. The analysis of the stability, robustness and the bounds on the parameters which guarantee convergence is conducted, and some practical issues relating the choice of parameters of the ALR-LMS and computational complexity are addressed. Comprehensive simulation results in the system identification and prediction setting support the analysis.