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2004

Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation

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Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation
An analog system-on-chip for kernel-based pattern classification and sequence estimation is presented. State transition probabilities conditioned on input data are generated by an integrated support vector machine. Dot product based kernels and support vector coefficients are implemented in analog programmable floating gate translinear circuits, and probabilities are propagated and normalized using sub-threshold current-mode circuits. A 14-input, 24-state, and 720-support vector forward decoding kernel machine is integrated on a 3mm
Shantanu Chakrabartty, Gert Cauwenberghs
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where NIPS
Authors Shantanu Chakrabartty, Gert Cauwenberghs
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