Abstract
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.
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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: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Fourth International Congress on Information and Communication Technology. Advances in Intelligent Systems and Computing, vol 1041. Springer, Singapore. https://doi.org/10.1007/978-981-15-0637-6_25
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DOI: https://doi.org/10.1007/978-981-15-0637-6_25
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