AN ANALOG CONTINUOUS-TIME NEURAL-NETWORK

An analog continuous-time neural network is described. Building blocks which include the capability for on-chip learning and an example network are described and test results are presented. We are using analog nonvolatile CMOS floating-gate memories for storage of the neural weights. The floating-gate memories are programmed by illuminating the entire chip with ultraviolet light. The subthreshold operation of the CMOS transistor in analog VLSI has a very low power dissipation which can be utilized to build larger computational systems, e.g., neural networks. The experimental results show that the floating-gate memories are promising, and that the building blocks are operating as separate units; however, especially the time constants involved in the computations of the continuous-time analog neural network should be studied further.