Herein, we propose a new class of stochastic gradient algorithm for channel identification. The proposed q-least mean fourth (q-LMF) is an extension of the least mean fourth (LMF) algorithm and it is based on the q-calculus which is also known as Jackson’s derivative. The proposed algorithm utilizes a novel concept of error correlation energy and normalization of signal to ensure a high convergence rate, better stability, and low steady-state error. Contrary to conventional LMF, the proposed method has more freedom for large step sizes. Extensive experiments show significant gain in the performance of the proposed q-LMF algorithm in comparison to the contemporary techniques.
CITATION STYLE
Sadiq, A., Usman, M., Khan, S., Naseem, I., Moinuddin, M., & Al-Saggaf, U. M. (2020). Q-lmf: Quantum calculus-based least mean fourth algorithm. In Advances in Intelligent Systems and Computing (Vol. 1041, pp. 303–311). Springer. https://doi.org/10.1007/978-981-15-0637-6_25
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