Vector quantization and signal compression
Vector quantization and signal compression
The Pattern Recognition Basis of Artificial Intelligence
The Pattern Recognition Basis of Artificial Intelligence
Microprocessors & Microsystems
K-means clustering algorithm for multimedia applications with flexible HW/SW co-design
Journal of Systems Architecture: the EUROMICRO Journal
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A fully-parallel minimum Manhattan-distance search associative memory has been designed in 0.35μm CMOS with 3-metal layers. The nearest-match unit consumes only 1.02mm2, while the chip area is 7.49mm2. The measured winner-search time of this chip, the time to determine the best-matching reference-data word for an input-data word among a database of 128 reference words (5-bit, 16 units), is 2, if a 32-bit computer with the same chip area would have to run the same workload. Furthermore the power dissipation of the designed test chip is only about 26.7mW/mm2.