69 citations · 105 across the 23 of their papers we have counts for
7 papers · 1 filter
A Weighted Generalized Coherence Approach for Sensing Matrix Design
Ameya Anjarlekar, Ajit Rajwade
As compared to using randomly generated sensing matrices, optimizing the sensing matrix w.r.t. a carefully designed criterion is known to lead to better quality signal recovery giv…
Contact Tracing Information Improves the Performance of Group Testing Algorithms
Ritesh Goenka, Shu-Jie Cao, Chau-Wai Wong +2
Group testing can help maintain a widespread testing program using fewer resources amid a pandemic. In group testing, we are given samples, one per individual. These samples ar…
Analyzing Cross Validation In Compressed Sensing With Mixed Gaussian And Impulse Measurement Noise With L1 Errors
Chinmay Gurjarpadhye, Shubhang Bhatnagar, Ajit Rajwade
Compressed sensing (CS) involves sampling signals at rates less than their Nyquist rates and attempting to reconstruct them after sample acquisition. Most such algorithms have para…
Signal Recovery in Perturbed Fourier Compressed Sensing
Eeshan Malhotra, Himanshu Pandotra, Ajit Rajwade +1
In many applications in compressed sensing, the measurement matrix is a Fourier matrix, i.e., it measures the Fourier transform of the underlying signal at some specified `base' fr…
Optimizing Matrices For Compressed Sensing Using Existing Goodness Measures: Negative Results, And An Alternative
Alankar Kotwal, Ajit Rajwade
The bound that arises out of sparse recovery analysis in compressed sensing involves input signal sparsity and some property of the sensing matrix. An effort has therefore been mad…
Reconstruction Error Bounds for Compressed Sensing under Poisson or Poisson-Gaussian Noise Using Variance Stabilization Transforms
Deepak Garg, Pakshal Bohra, Karthik S. Gurumoorthy +1
Most existing bounds for signal reconstruction from compressive measurements make the assumption of additive signal-independent noise. However in many compressive imaging systems,…
Reconstruction Error Bounds for Compressed Sensing under Poisson Noise using the Square Root of the Jensen-Shannon Divergence
Sukanya Patil, Karthik Gurumoorthy, Ajit Rajwade
Reconstruction error bounds in compressed sensing under Gaussian or uniform bounded noise do not translate easily to the case of Poisson noise. Reasons for this include the signal…