LS-CS-Residual (LS-CS): Compressive Sensing on Least Squares Residual
نویسندگان
چکیده
منابع مشابه
Stability of LS-CS-residual and modified-CS for sparse signal sequence reconstruction
In this work, we show the “stability” of two of our recently proposed algorithms, LS-CS-residual (LS-CS) and the noisy version of modified-CS, designed for recursive reconstruction of sparse signal sequences from noisy measurements. By “stability” we mean that the number of misses from the current support estimate and the number of extras in it remain bounded by a time-invariant value at all ti...
متن کاملKF-CS: Compressive Sensing on Kalman Filtered Residual
We consider the problem of recursively reconstructing time sequences of sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear incoherent measurements with additive noise. The idea of our proposed solution, KF CS-residual (KFCS) is to replace compressed sensing (CS) on the observation by CS on the Kalman filtered (KF) observation residual computed using...
متن کاملExtended Least Squares LS–SVM
Among neural models the Support Vector Machine (SVM) solutions are attracting increasing attention, mostly because they eliminate certain crucial questions involved by neural network construction. The main drawback of standard SVM is its high computational complexity, therefore recently a new technique, the Least Squares SVM (LS–SVM) has been introduced. In this paper we present an extended vie...
متن کاملStability of Modified-CS and LS-CS for Recursive Reconstruction of Sparse Signal Sequences
In this work, we obtain sufficient conditions for the “stability” of our recently proposed algorithms, Least Squares Compressive Sensing residual (LS-CS) and modified-CS, for recursively reconstructing sparse signal sequences from noisy measurements. By “stability” we mean that the number of misses from the current support estimate and the number of extras in it remain bounded by a time-invaria...
متن کاملStability (over time) of Modified-CS and LS-CS for Recursive Causal Sparse Reconstruction
In this work, we obtain sufficient conditions for the “stability” of our recently proposed algorithms, modified-CS (for noisy measurements) and Least Squares CS-residual (LS-CS), designed for recursive reconstruction of sparse signal sequences from noisy measurements. By “stability” we mean that the number of misses from the current support estimate and the number of extras in it remain bounded...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2010
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2010.2048105