Zobrazeno 11 - 20
of 195
pro vyhledávání: '"Naseem, Imran"'
Autor:
Ibrahim, Shakeel Muhammad, Ibrahim, Muhammad Sohail, Usman, Muhammad, Naseem, Imran, Moinuddin, Muhammad
Heart is one of the vital organs of human body. A minor dysfunction of heart even for a short time interval can be fatal, therefore, efficient monitoring of its physiological state is essential for the patients with cardiovascular diseases. In the re
Externí odkaz:
http://arxiv.org/abs/1911.09332
Publikováno v:
2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology (ICEEST)
Herein, we propose a spatio-temporal extension of RBFNN for nonlinear system identification problem. The proposed algorithm employs the concept of time-space orthogonality and separately models the dynamics and nonlinear complexities of the system. T
Externí odkaz:
http://arxiv.org/abs/1908.01321
Publikováno v:
Circuits, Systems, and Signal Processing, vol. 36, no. 4, pp. 1639-1653, 2017
In this paper, we propose a novel adaptive kernel for the radial basis function (RBF) neural networks. The proposed kernel adaptively fuses the Euclidean and cosine distance measures to exploit the reciprocating properties of the two. The proposed fr
Externí odkaz:
http://arxiv.org/abs/1905.03546
Autor:
Sadiq, Alishba, Usman, Muhammad, Khan, Shujaat, Naseem, Imran, Moinuddin, Muhammad, Al-Saggaf, Ubaid M.
Channel estimation is an essential part of modern communication systems as it enhances the overall performance of the system. In recent past a variety of adaptive learning methods have been designed to enhance the robustness and convergence speed of
Externí odkaz:
http://arxiv.org/abs/1812.02588
Publikováno v:
"RAFP-Pred: Robust Prediction of Antifreeze Proteins Using Localized Analysis of n-Peptide Compositions," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 15, no. 1, pp. 244-250, 1 Jan.-Feb. 2018
In extreme cold weather, living organisms produce Antifreeze Proteins (AFPs) to counter the otherwise lethal intracellular formation of ice. Structures and sequences of various AFPs exhibit a high degree of heterogeneity, consequently the prediction
Externí odkaz:
http://arxiv.org/abs/1809.09620
Akademický článek
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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. Our apprehensions are based on the evidence we found in the derivation and
Externí odkaz:
http://arxiv.org/abs/1805.07640
The purpose of this note is to discuss some aspects of recently proposed fractional-order variants of complex least mean square (CLMS) and normalized least mean square (NLMS) algorithms in ``Design of Fractional-order Variants of Complex LMS and Norm
Externí odkaz:
http://arxiv.org/abs/1802.09252
In this work, a new class of stochastic gradient algorithm is developed based on $q$-calculus. Unlike the existing $q$-LMS algorithm, the proposed approach fully utilizes the concept of $q$-calculus by incorporating time-varying $q$ parameter. The pr
Externí odkaz:
http://arxiv.org/abs/1801.00410
Publikováno v:
2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA), Batu Ferringhi, 2017, pp. 1-6
In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable step size-FLMS (RVSS-FLMS), dynamically updates the step size of the FLM
Externí odkaz:
http://arxiv.org/abs/1711.04973