A 1.2mW on-line learning mixed mode intelligent inference engine for robust object recognition

An intelligent inference engine (IIE) is proposed as a controller for low power high speed robust object recognition processor. It contains analog digital mixed mode neuro-fuzzy circuits for the on-line learning to increase attention efficiency. It is implemented in 0.13um CMOS process and achieves 1.2mW power consumption with 94% average classification accuracy within 1us operation. The 0.765mm² IIE achieves 76% attention efficiency, and reduces power and processing delay of the 50mm² recognition processor by up to 37% and 28%, respectively, with 96% recognition accuraacy.