In SICD, the localization fingerprint reflecting the time–frequency and space–frequency characteristics of CSI-MIMO under a single access point (AP) was first designed. Then, we developed a dimensionality reduction algorithm to map the high-dimensional CSI-MIMO amplitude data to a low-dimensional space.
To reduce the redundancy in the data of CSI-MIMO amplitude, we developed a data dimensionality reduction algorithm. Moreover, by leveraging a ...
Feb 9, 2021 · To reduce the redundancy in the data of CSI-MIMO amplitude, we developed a data dimensionality reduction algorithm. Moreover, by leveraging ...
Jul 25, 2024 · From: Journal of Engineering ; Publisher: NewsRX LLC ; Document Type: Financial report; Brief article ; Length: 403 words ; Lexile Measure: 1160L ...
SICD: Novel Single-Access-Point Indoor Localization Based on CSI-MIMO with Dimensionality Reduction ; Yunwei Zhang, Weigang Wang, Chendong Xu, Jie Qin, Shujuan ...
SICD: Novel Single-Access-Point Indoor Localization Based on CSI-MIMO with Dimensionality Reduction. Sensors 2021, 21, 1325. https://doi.org/10.3390 ...
SICD: Novel Single-Access-Point Indoor Localization Based on CSI-MIMO with Dimensionality Reduction. Sensors. 2021-02-13 | Journal article. DOI: 10.3390 ...
In this study, the sensitivity of CSI is first analysed and stable CSI fingerprints can be obtained by reducing the variance from interference and white noise.
SICD: Novel single-access-point indoor localization based on CSI-MIMO with dimensionality reduction · Low-rank sparse feature selection for image classification.
SICD: Novel Single-Access-Point Indoor Localization Based on CSI-MIMO with Dimensionality Reduction · Computer Science, Engineering. Sensors · 2021.