activity
20172021
most citedA Novel Adaptive Kernel for the RBF Neural Networks

44 citations · 67 across the 6 of their papers we have counts for

collaborators

8 papers

cs.IT2021

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…

cs.LG20212 cited

q-RBFNN:A Quantum Calculus-based RBF Neural Network

Syed Saiq Hussain, Muhammad Usman, Taha Hasan Masood Siddique +3

In this research a novel stochastic gradient descent based learning approach for the radial basis function neural networks (RBFNN) is proposed. The proposed method is based on the…

cs.LG2020

Multi-Kernel Fusion for RBF Neural Networks

Syed Muhammad Atif, Shujaat Khan, Imran Naseem +2

A simple yet effective architectural design of radial basis function neural networks (RBFNN) makes them amongst the most popular conventional neural networks. The current generatio…

eess.IV20193 cited

Heart Segmentation From MRI Scans Using Convolutional Neural Network

Shakeel Muhammad Ibrahim, Muhammad Sohail Ibrahim, Muhammad Usman +2

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…

stat.ML2019

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…

stat.ML201944 cited

A Novel Adaptive Kernel for the RBF Neural Networks

Shujaat Khan, Imran Naseem, Roberto Togneri +1

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 measur…