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Design of a multi-core hardware architecture for consensus-based MIMO detection algorithms.

, , , and . ACSSC, page 877-881. IEEE, (2016)

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Structure reconstruction of correlated neural signals based on inpainting for brain monitoring., , , and . BioCAS, page 1-4. IEEE, (2015)High-performance bivariate numeric function approximation for hardware-efficient QR-decomposition., , and . ICECS, page 257-260. IEEE, (2016)Compressed sensing K-best detection for sparse multi-user communications., , , , , and . EUSIPCO, page 1726-1730. IEEE, (2014)Low-complexity and approximative sphere decoding of sparse signals., , and . ACSCC, page 1241-1244. IEEE, (2012)Hardware-Efficient QR-Decomposition Using Bivariate Numeric Function Approximation., , , and . IEEE Trans. Circuits Syst. I Regul. Pap., 64-I (12): 3150-3159 (2017)Activity and Channel Estimation in Multi-User Wireless Sensor Networks., , , and . WSA, page 1-5. VDE-Verlag / IEEE, (2016)High throughput architecture for inpainting-based recovery of correlated neural signals., , , , , and . EUSIPCO, page 1728-1732. IEEE, (2016)Exploiting correlation in neural signals for data compression., , , , , , and . EUSIPCO, page 2080-2084. IEEE, (2014)Hardware-accelerated reconstruction of compressed neural signals based on inpainting., , , , , , and . MIXDES, page 399-404. IEEE, (2016)Design of a multi-core hardware architecture for consensus-based MIMO detection algorithms., , , and . ACSSC, page 877-881. IEEE, (2016)