13 citations · 27 across the 6 of their papers we have counts for
6 papers
A Novel Quantum Calculus-based Complex Least Mean Square Algorithm (q-CLMS)
Alishba Sadiq, Imran Naseem, Shujaat Khan +3
In this research, a novel adaptive filtering algorithm is proposed for complex domain signal processing. The proposed algorithm is based on Wirtinger calculus and is called as q-Co…
Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks
Alishba Sadiq, Muhammad Sohail Ibrahim, Muhammad Usman +2
Due to the dynamic nature, chaotic time series are difficult predict. In conventional signal processing approaches signals are treated either in time or in space domain only. Spati…
Spatio-Temporal RBF Neural Networks
Shujaat Khan, Jawwad Ahmad, Alishba Sadiq +2
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 sepa…
q-LMF: Quantum Calculus-based Least Mean Fourth Algorithm
Alishba Sadiq, Muhammad Usman, Shujaat Khan +3
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…
Comments on "Momentum fractional LMS for power signal parameter estimation"
Shujaat Khan, Imran Naseem, Alishba Sadiq +2
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…
Enhanced -Least Mean Square
Shujaat Khan, Alishba Sadiq, Imran Naseem +2
In this work, a new class of stochastic gradient algorithm is developed based on -calculus. Unlike the existing -LMS algorithm, the proposed approach fully utilizes the conce…