4 citations · 6 across the 5 of their papers we have counts for
5 papers
Weakly-Convex Regularization for Magnetic Resonance Image Denoising
Akash Prabakar, Abhishek Shreekant Bhandiwad, Abijith Jagannath Kamath +1
Regularization for denoising in magnetic resonance imaging (MRI) is typically achieved using convex regularization functions. Recently, deep learning techniques have been shown to…
Neuromorphic Sampling of Sparse Signals
Abijith Jagannath Kamath, Chandra Sekhar Seelamantula
Neuromorphic sampling is a bioinspired and opportunistic analog-to-digital conversion technique, where the measurements are recorded only when there is a significant change in the…
Tight-frame-like Analysis-Sparse Recovery Using Non-tight Sensing Matrices
Kartheek Kumar Reddy Nareddy, Abijith Jagannath Kamath, Chandra Sekhar Seelamantula
The choice of the sensing matrix is crucial in compressed sensing. Random Gaussian sensing matrices satisfy the restricted isometry property, which is crucial for solving the spars…
Neuromorphic Sampling of Signals in Shift-Invariant Spaces
Abijith Jagannath Kamath, Chandra Sekhar Seelamantula
Neuromorphic sampling is a paradigm shift in analog-to-digital conversion where the acquisition strategy is opportunistic and measurements are recorded only when there is a signifi…
Time Encoding of Finite-Rate-of-Innovation Signals
Abijith Jagannath Kamath, Sunil Rudresh, Chandra Sekhar Seelamantula
Time-encoding of continuous-time signals is an alternative sampling paradigm to conventional methods such as Shannon's sampling. In time-encoding, the signal is encoded using a seq…