Identification of clusters in the fingerprinting method using power measurements
2014
Detection method plays important role in applications of high frequencies techniques for locations systems. One of the most popular techniques is the fingerprinting that operates the relationship between signals. It is considered that in each point in the building has a unique fingerprint or received power by the access points. In this work it was made measurements into an office scenario and it was used cluster identification method to define the fingerprints. Two clustering algorithms, k-means and rek-means was implemented in order to compare both methods.
Keywords:
- Electronic engineering
- Clustering high-dimensional data
- Cluster analysis
- Consensus clustering
- Determining the number of clusters in a data set
- Correlation clustering
- Artificial intelligence
- FLAME clustering
- Canopy clustering algorithm
- CURE data clustering algorithm
- Machine learning
- Computer science
- Pattern recognition
- k-means clustering
- DBSCAN
- Fingerprint
- Data mining
- Correction
- Source
- Cite
- Save
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