Ara
Toplam kayıt 2, listelenen: 1-2
Compressed spectrum sensing using sparse recovery convergence patterns through machine learning classification
(Institute of Electrical and Electronics Engineers Inc., 2019)
Despite the well-known success of sub-Nyquist sampling in reducing the hardware and computational costs of spectrum sensing, it still has the shortcoming of requiring a pre-determined spectrum sparsity level. This paper ...
Exploiting sparsity recovery for compressive spectrum sensing: A machine learning approach
(Institute of Electrical and Electronics Engineers Inc., 2019)
Sub-Nyquist sampling for spectrum sensing has the advantages of reducing the sampling and computational complexity burdens. However, determining the sparsity of the underlying spectrum is still a challenging issue for this ...