| Title | Performance Comparison of Orthogonal Matching Pursuit and Novel Incremental Gaussian Elimination OMP Reconstruction Algorithms for Compressive Sensing |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Prasad Reddy, V H, Kishore Kumar, Puli |
| Conference Name | 2021 IEEE International Conference on Microwaves, Antennas, Communications and Electronic Systems (COMCAS) |
| Keywords | composability, compressive sampling, compressive sensing, Hardware, Matching pursuit algorithms, mean square error methods, Microwave antennas, Microwave measurement, orthogonal matching pursuit, pubcrawl, RD-AIC, Reconstruction algorithms, resilience, Resiliency, Signal processing algorithms |
| Abstract | Compressive Sensing (CS) is a promising investigation field in the communication signal processing domain. It offers an advantage of compression while sampling; hence, data redundancy is reduced and improves sampled data transmission. Due to the acquisition of compressed samples, Analog to Digital Conversions (ADCs) performance also improved at ultra-high frequency communication applications. Several reconstruction algorithms existed to reconstruct the original signal with these sub-Nyquist samples. Orthogonal Matching Pursuit (OMP) falls under the category of greedy algorithms considered in this work. We implemented a compressively sensed sampling procedure using a Random Demodulator Analog-to-Information Converter (RD-AIC). And for CS reconstruction, we have considered OMP and novel Incremental Gaussian Elimination (IGE) OMP algorithms to reconstruct the original signal. Performance comparison between OMP and IGE OMP presented. |
| DOI | 10.1109/COMCAS52219.2021.9629027 |
| Citation Key | prasad_reddy_performance_2021 |
Performance Comparison of Orthogonal Matching Pursuit and Novel Incremental Gaussian Elimination OMP Reconstruction Algorithms for Compressive Sensing