RSS Fingerprints Based Distributed Semi-Supervised Locally Linear Embedding (DSSLLE) Location Estimation System for Indoor WLAN

Author:

Jain Vinod Kumar,Tapaswi Shashikala,Shukla Anupam

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Reference23 articles.

1. Ahmad, U., Gavrilov, A., Lee, S., & Lee, Y. (2008). A modular classification model for received signal strength based location systems. Neuro Computing, 71(13–15).

2. Ahmad U., Gavrilov A., Lee Y., Lee S. (2008) Context-aware, self-scaling Fuzzy ArtMap for received signal strength based location systems. Soft Computing-A Fusion of Foundations, Methodologies and Applications 12(7): 699–713

3. Bahl, P., & Padmanabhan, V. (2000). RADAR: An in-building RF-based user location and tracking system. In Proceedings of 19th IEEE annual joint conference of computer and communications societies, INFOCOM 2000 (Vol. 2, pp. 775–784).

4. Bahl, P., Padmanabhan, V., & Balachandran, A. (2000). Enhancements to the RADAR user location and tracking system. Microsoft Research (MSR-TR-2000-12), 13.

5. Battiti, R., Nhat, T., & Villani, A. (2002). Location-aware computing: A neural network model for determining location in wireless LANs. Technical Report DIT-02-083, Ingegneria e Scienza dell’Informazione, University of Trento.

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