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Application-level Studies of Cellular Neural Network-based Hardware Accelerators

By Qiuwen Lou and others
As cost and performance benefits associated with Moore's Law scaling slow, researchers are studying alternative architectures (e.g., based on analog and/or spiking circuits) and/or computational models (e.g., convolutional and recurrent neural networks) to perform application-level tasks faster, more energy efficiently, and/or more accurately. We investigate cellular neural network (CeNN)-based co-processors... Show more
June 12, 2019
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Application-level Studies of Cellular Neural Network-based Hardware Accelerators
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