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Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks
The proposed RBF architecture is explored for the prediction of Mackey-Glass time series and results are compared with the standard RBF.
Spatio-Temporal RBF Neural Networks
Herein, we propose a spatio-temporal extension of RBFNN for nonlinear system identification problem.
q-LMF: Quantum Calculus-based Least Mean Fourth Algorithm
The proposed $q$-least mean fourth ($q$-LMF) is an extension of least mean fourth (LMF) algorithm and it is based on the $q$-calculus which is also known as Jackson derivative.
Comments on "Momentum fractional LMS for power signal parameter estimation"
The purpose of this paper is to indicate that the recently proposed Momentum fractional least mean squares (mFLMS) algorithm has some serious flaws in its design and analysis.
