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Creators/Authors contains: "Heredia-Juesas, Juan"

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  1. ; ; ; (, Passive and Active Millimeter-Wave Imaging XXV)
    Robertson, Duncan A.; Wikner, David A. (Ed.)
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  2. ; ; ; (, IEEE Transactions on Microwave Theory and Techniques)
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  3. ; ; ; (, IEEE Transactions on Microwave Theory and Techniques)
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  4. ; ; ; (, IEEE Transactions on Computational Imaging)
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  5. ; ; ; (, IEEE Antennas and Wireless Propagation Letters)
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  6. ; ; ; ; (, IEEE Access)
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  7. ; ; (, 2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting)
    Norm-1 regularized optimization algorithms are commonly used for Compressive Sensing applications. In this paper, an optimization algorithm based on the Alternating Direction Method of Multipliers (ADMM) together with the Elastic Net regularization is presented. This type of regularization is a linear combination of the norm-1 and norm-2 regularizations,allowing a solution between the sparsest and the minimum energy solutions, but still enforcing some sparsivity. The combination of these two regularizations and the distributive capabilities of the ADMM algorithm enables a fast sparse signal recovering with minimum error. 
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  8. ; ; ; (, 2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting)
    This paper presents a norm-1 regularized algorithm, based on the Alternating Direction Method of Multipliers(ADMM), in which the sensing matrix is divided by columns. This technique is based on sectioning the imaging domain into different regions and optimizing them in distributed computational nodes.The information shared among nodes is highly reduced compared to the consensus-based ADMM, when dividing the matrix by rows. The combination of the sectioning-based ADMM with the imaging capabilities of the recently proposed Compressive Reflector Antenna allows a distributed, real-time imaging with fast node communication. 
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  9. ; ; ; ; (, 2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting)
    This paper explores the use of compressive sensing (CS) methods to microwave-induced thermoacoustics (TA)imaging. Moreover, it proposes the use of a holey cavity as a mechanism to enhance the reconstruction properties of the sensing matrix. The CS imaging and the holey cavity reduce the number of measurements needed to perform the imaging, thus reducing the overall complexity of the imaging system. 
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  10. ; ; ; ; ; ; ; (, IEEE Antennas and Wireless Propagation Letters)
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