890 citations · 3k across the 39 of their papers we have counts for
4 papers · 1 filter
A Generalized Proportionate-Type Normalized Subband Adaptive Filter
Kuan-Lin Chen, Ching-Hua Lee, Bhaskar D. Rao +1
We show that a new design criterion, i.e., the least squares on subband errors regularized by a weighted norm, can be used to generalize the proportionate-type normalized subband a…
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
Kuan-Lin Chen, Ching-Hua Lee, Harinath Garudadri +1
Models recently used in the literature proving residual networks (ResNets) are better than linear predictors are actually different from standard ResNets that have been widely used…
A Novel Bayesian Approach for the Two-Dimensional Harmonic Retrieval Problem
Rohan R. Pote, Bhaskar D. Rao
Sparse signal recovery algorithms like sparse Bayesian learning work well but the complexity quickly grows when tackling higher dimensional parametric dictionaries. In this work we…
General Total Variation Regularized Sparse Bayesian Learning for Robust Block-Sparse Signal Recovery
Aditya Sant, Markus Leinonen, Bhaskar D. Rao
Block-sparse signal recovery without knowledge of block sizes and boundaries, such as those encountered in multi-antenna mmWave channel models, is a hard problem for compressed sen…