45 citations · 196 across the 31 of their papers we have counts for
6 papers · 1 filter
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…
Adaptive and Compressive Beamforming Using Deep Learning for Medical Ultrasound
Shujaat Khan, Jaeyoung Huh, Jong Chul Ye
In ultrasound (US) imaging, various types of adaptive beamforming techniques have been investigated to improve the resolution and contrast-to-noise ratio of the delay and sum (DAS)…
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…
Deep Learning-based Universal Beamformer for Ultrasound Imaging
Shujaat Khan, Jaeyoung Huh, Jong Chul Ye
In ultrasound (US) imaging, individual channel RF measurements are back-propagated and accumulated to form an image after applying specific delays. While this time reversal is usua…
Universal Deep Beamformer for Variable Rate Ultrasound Imaging
Shujaat Khan, Jaeyoung Huh, Jong Chul Ye
Ultrasound (US) imaging is based on the time-reversal principle, in which individual channel RF measurements are back-propagated and accumulated to form an image after applying spe…