WLAN Indoor Positioning Based on D-LDA Feature Extraction Algorithm
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Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-10-6571-2_336
Reference8 articles.
1. Laitinen, E., Talvitie, J., Lohan, E.S.: On the RSS biases in WLAN-based indoor positioning. In: ANLN Workshop at ICC 2015, pp. 1–6 (2015)
2. Abusara, A., Hassan, M.: Enhanced fingerprinting in WLAN-based indoor positioning using hybrid search techniques. In: International Conference on Communications, Signal Processing, and their Applications, pp. 1–6. IEEE (2015)
3. Talvitie, J., Renfors, M., Lohan, E.S.: A comparison of received signal strength statistics between 2.4 GHz and 5 GHz bands for WLAN-based indoor positioning. In: IEEE GLOBECOM Workshops 2015, pp. 1–6 (2015)
4. Yang, M., Wan, J., Ji, G.: Random sampling LDA incorporating feature selection for face recognition. In: Proceedings of the 2010 International Conference on Wavelet Analysis and Pattern Recognition, pp. 11–14 (2010)
5. Ye, Y., Yang, J.: A direct LDA algorithm for high-dimensional data with application to face recognition. Pattern Recogn. 34, 2067–2070 (2001)
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