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Greedy Algorithms for Non-linear Sparse Recovery

  • Kavya Gupta
  • Angshul Majumdar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 390)

Abstract

In this work we propose two greedy algorithms to solve the underdetermined nonlinear sparse recovery problem. There are hardly any algorithms to solve such problems. Our algorithm is based on the OMP (Orthogonal Matching Pursuit) and the CoSaMP (Compressive Sampling Matching Pursuit), two popular techniques for solving the linear problem. We empirically test the success rates of our algorithms on exponential and logarithmic functions. The success rates follow a pattern similar to the one we observe for linear recovery problems.

Keywords

Compressed sensing EEG WBAN 

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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Indraprastha Institute of Information TechnologyNew DelhiIndia

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