Adapa, Bhagyaraja, Biswas, Dwaipayan, Bhardwaj, Swati, Raghuraman, Shashank, Acharyya, Amit and Maharatna, Koushik (2017) Coordinate rotation based low complexity K-means clustering architecture. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 25 (4), 1568-1572. (doi:10.1109/TVLSI.2016.2633543).
Abstract
In this brief, we propose a low-complexity architectural implementation of the K-means-based clustering algorithm used widely in mobile health monitoring applications for unsupervised and supervised learning. The iterative nature of the algorithm computing the distance of each data point from a respective centroid for a successful cluster formation until convergence presents a significant challenge to map it onto a low-power architecture. This has been addressed by the use of a 2-D Coordinate Rotation Digital Computer-based low-complexity engine for computing the n-dimensional Euclidean distance involved during clustering. The proposed clustering engine was synthesized using the TSMC 130-nm technology library, and a place and route was performed following which the core area and power were estimated as 0.36 mm2 and 9.21 mW at 100 MHz, respectively, making the design applicable for low-power real-time operations within a sensor node.
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- Faculties (pre 2018 reorg) > Faculty of Physical Sciences and Engineering (pre 2018 reorg) > Electronics & Computer Science (pre 2018 reorg) > Cyber Physical Systems (pre 2018 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg) > Cyber Physical Systems (pre 2018 reorg)
School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg) > Cyber Physical Systems (pre 2018 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science > Cyber Physical Systems > Cyber Physical Systems (pre 2018 reorg)
School of Electronics and Computer Science > Cyber Physical Systems > Cyber Physical Systems (pre 2018 reorg) - Faculties (pre 2018 reorg) > Faculty of Physical Sciences and Engineering (pre 2018 reorg) > Electronics & Computer Science (pre 2018 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg)
School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg)
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