Add to ORKGMI: Global COE Program Education-and-Research Hub for Mathematics-for-IndustryグローバルCOEプログラム「マス･フォア･インダストリ教育研究拠点」This paper introduces a new general theory of compressed sensing. We give a natural generalization of the restricted isometry property (RIP) called weak RIP. We consider the proposed theory to be more useful for real data analysis than the RIP. In this note, we verify the accuracy of the weak RIP by showing in reconstruction from undersampling measurements where it is possible to improve estimation in various situations
This paper proposes greedy numerical schemes to compute lower bounds of the restricted isometry cons...
Abstract—This paper proposes greedy numerical schemes to compute lower bounds of the restricted isom...
In this paper, we provide a new approach to estimating the error of re-construction from Σ ∆ quantiz...
This paper introduces a new general theory of compressed sensing. We give a natural generalization o...
MI: Global COE Program Education-and-Research Hub for Mathematics-for-IndustryグローバルCOEプログラム「マス･フォア･イ...
This paper introduce simple and general theories of compressed sensing and LASSO. The novelty is tha...
Compressed sensing (CS) seeks to recover an unknown vector with N entries by making far fewer than N...
Abstract. Compressed Sensing (CS) seeks to recover an unknown vector with N entries by making far fe...
The Restricted Isometry Property (RIP) introduced by Candés and Tao is a fundamental property in co...
This paper introduce simple and general theories of compressed sensing and LASSO. The novelty is tha...
Compressive Sampling (CS) describes a method for reconstructing high-dimensional sparse signals from...
This paper establishes new sufficient conditions on the restricted isometry property (RIP) for compr...
This paper establishes new sufficient conditions on the restricted isometry property (RIP) for compr...
This paper proposes greedy numerical schemes to compute lower bounds of the restricted isometry cons...
International audienceThis paper proposes greedy numerical schemes to compute lower bounds of the re...
This paper proposes greedy numerical schemes to compute lower bounds of the restricted isometry cons...
Abstract—This paper proposes greedy numerical schemes to compute lower bounds of the restricted isom...
In this paper, we provide a new approach to estimating the error of re-construction from Σ ∆ quantiz...
This paper introduces a new general theory of compressed sensing. We give a natural generalization o...
MI: Global COE Program Education-and-Research Hub for Mathematics-for-IndustryグローバルCOEプログラム「マス･フォア･イ...
This paper introduce simple and general theories of compressed sensing and LASSO. The novelty is tha...
Compressed sensing (CS) seeks to recover an unknown vector with N entries by making far fewer than N...
Abstract. Compressed Sensing (CS) seeks to recover an unknown vector with N entries by making far fe...
The Restricted Isometry Property (RIP) introduced by Candés and Tao is a fundamental property in co...
This paper introduce simple and general theories of compressed sensing and LASSO. The novelty is tha...
Compressive Sampling (CS) describes a method for reconstructing high-dimensional sparse signals from...
This paper establishes new sufficient conditions on the restricted isometry property (RIP) for compr...
This paper establishes new sufficient conditions on the restricted isometry property (RIP) for compr...
This paper proposes greedy numerical schemes to compute lower bounds of the restricted isometry cons...
International audienceThis paper proposes greedy numerical schemes to compute lower bounds of the re...
This paper proposes greedy numerical schemes to compute lower bounds of the restricted isometry cons...
Abstract—This paper proposes greedy numerical schemes to compute lower bounds of the restricted isom...
In this paper, we provide a new approach to estimating the error of re-construction from Σ ∆ quantiz...