Dec 5, 2011 · In this Letter we investigate the application of sparse spectrum Gaussian process (SSGP) to the multiuser detection problem. The key point of ...
The key point of the SSGP is that the sparsity of spectral representation of Gaussian process leads to an algorithm with much lower complexity than the full. GP ...
Oct 22, 2024 · In this Letter we investigate the application of sparse spectrum Gaussian process (SSGP) to the multiuser detection problem. The key point of ...
Researchr is a web site for finding, collecting, sharing, and reviewing scientific publications, for researchers by researchers. Sign up for an account to ...
Apr 1, 2024 · In this paper, the fault detection of a variable displacement pump under random time-variant working conditions is investigated for the first time.
This paper proposes Gaussian processes for Regression for constructing analytical nonlinear multiuser detectors in CDMA communication systems and shows that ...
Apr 25, 2024 · Shaowei Wang, Hualai Gu: Multiuser Detection with Sparse Spectrum Gaussian Process Regression. IEEE Commun. Lett. 16(2): 164-167 (2012) ...
The sparse Gaussian process regression (GPR) model that reduces the complexity of full GPR is employed for wind gust forecasting by combining numerical weather ...
Abstract. We present a new sparse Gaussian Process (GP) model for regression. The key novel idea is to sparsify the spectral representation of the GP.
Missing: Multiuser | Show results with:Multiuser
Abstract—In this paper we present Gaussian processes for. Regression (GPR) as a novel detector for CDMA digital com- munications.