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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Vivekanand, V. Vidya, L. |
| Copyright Year | 2014 |
| Description | Author affiliation: Vikram Sarabhai Space Centre, ISRO, Thiruvananthapuram, India (Vivekanand, V.; Vidya, L.) |
| Abstract | Analysis of cascade network consisting of RBF nodes and least square error minimization block for compressed sensing recovery of sparse signals is presented in this paper. The proposed algorithm radial basis function cascade network for sparse signal recovery uses the $L_{0}$ norm optimization, $L_{2}$ least square method and feedback network model to improve the signal recovery performance and computational time over the existing ANN based and SL0 algorithms. The recovery of spike and pulse current measurement from simulated compressed sensed data for Telemetry application is demonstrated using the new algorithm. The Simulink model for compressed sensing data acquisition process, sparse signal recovery results and algorithm performance evaluation are presented. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 375153 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479946655 |
| DOI | 10.1109/SPCOM.2014.6983938 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-07-22 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis ANN CS measurement Noise Artificial neural networks Compressed Sensing RASR Minimization Noise measurement Telemetry Convergence RBF Approximation algorithms |
| Content Type | Text |
| Resource Type | Article |
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