TY  - GEN
KW  - Array synthesis 
KW  -  Bayesian compressive sampling (BCS) 
KW  -  linear arrays 
KW  -  relevance vector machine 
KW  -  sparse arrays
AV  - public
ID  - elediasc12505
A1  - Oliveri, Giacomo
A1  - Massa, Andrea
N2  - A numerically-efficient technique based on the Bayesian compressive sampling (BCS) for the design of maximally-sparse linear arrays is introduced. The method is based on a probabilistic formulation of the array synthesis and it exploits a fast relevance vector machine (RVM) for the problem solution. The proposed approach allows the design of linear arrangements fitting desired power patterns with a reduced number of non-uniformly spaced active elements. The numerical validation assesses the effectiveness and computational efficiency of the proposed approach as a suitable complement to existing state-of-the-art techniques for the design of sparse arrays. ?(c) 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.?
UR  - http://www.eledia.org/students-reports/505/
Y1  - 2011/01//
TI  - Bayesian Compressive Sampling for Pattern Synthesis With Maximally Sparse Non-Uniform Linear Arrays
ER  -