A linearly convergent algorithm for sparse signal reconstruction
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Fixed Point Theory and Applications"
DOI: 10.1007/s11784-018-0635-1
Abstract: For the sparse signal reconstruction problem in compressive sensing, we propose a projection-type algorithm without any backtracking line search based on a new formulation of the problem. Under suitable conditions, global convergence and its linear… read more here.
Keywords: sparse signal; algorithm sparse; signal reconstruction; linearly convergent ... See more keywords
A new greedy algorithm for sparse recovery
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.05.022
Abstract: Abstract Compressed sensing (CS) has been one of the great successes of applied mathematics in the last decade. This paper proposes a new method, combining the advantage of the Compressive Sampling Matching Pursuit (CoSaMP) algorithm… read more here.
Keywords: recovery; algorithm; greedy algorithm; algorithm sparse ... See more keywords
Improved Variable Forgetting Factor Proportionate RLS Algorithm with Sparse Penalty and Fast Implementation Using DCD Iterations
Sign Up to like & getrecommendations! Published in 2024 at "China Communications"
DOI: 10.23919/jcc.ja.2022-0367
Abstract: the proportionate recursive least squares (PRLS) algorithm has shown faster convergence and better performance than both proportionate updating (PU) mechanism based least mean squares (LMS) algorithms and RLS algorithms with a sparse regularization term. In… read more here.
Keywords: proportionate; sparse penalty; fast implementation; forgetting factor ... See more keywords