Title :
Segmented compressed sampling for analog-to-information conversion
Author :
Taheri, Omid ; Vorobyov, Sergiy A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada
Abstract :
A new segmented compressed sampling method for analog-to-information conversion (AIC) is proposed. According to this method, signal is first segmented and passed through the AIC to generate an array of incomplete measurements. Then, an extended number of correlated measurements is constructed by adding up subsets of the incomplete measurements selected in a specific manner. Due to the inherent special structure of the method, the complexity of the sampling device is unchanged, while the signal recovery performance is significantly improved. The validity of the proposed method is justified through theoretical analysis. Simulation results also verify the effectiveness of the proposed segmented compressed sampling method.
Keywords :
communication complexity; signal sampling; analog-to-information conversion; sampling device complexity; segmented compressed sampling method; signal recovery performance; theoretical analysis; Conferences; Image sampling; Matrix converters; Sampling methods; Signal design; Signal generators; Signal sampling; Sparse matrices; Sufficient conditions; Vectors; Compressed sampling; analog-to-information converter; restricted isometry property;
Conference_Titel :
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009 3rd IEEE International Workshop on
Conference_Location :
Aruba, Dutch Antilles
Print_ISBN :
978-1-4244-5179-1
Electronic_ISBN :
978-1-4244-5180-7
DOI :
10.1109/CAMSAP.2009.5413327