Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals that enables sampling rates significantly below the classical Nyquist rate. Based on...
Luisa F. Polania, Rafael E. Carrillo, Manuel Blanc...
Cross-lingual voice transformation is challenging when source language (L1) and target language (L2) are very different in corresponding phonetics and prosodies. We propose a fram...
Due to multipath delay spread and relatively high sampling rate in OFDM systems, the channel estimation is formulated as a sparse recovery problem, where a hybrid compressed sensi...
Owing to the non-zero probability of the missed detection and false alarm of active primary transmission, a certain degree of performance degradation of the primary user (PU) from...
This paper considers an artificial noise (AN) aided secrecy rate maximization (SRM) problem for a multi-input single-output (MISO) channel overheard by multiple single-antenna ea...