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Analog resistive memories promise to reduce the energy of neural networks by orders of magnitude. However, the write variability and write nonlinearity of current devices prevent neural networks from training to high accuracy. We present a novel periodic carry method that uses a positional number system to overcome this while maintaining the benefit of parallel analog matrix operations. We demonstrate...
Neural machine learning methods, such as deep neural networks (DNN), have achieved remarkable success in a number of complex data processing tasks. These methods have arguably had their strongest impact on tasks such as image and audio processing — data processing domains in which humans have long held clear advantages over conventional algorithms. In contrast to biological neural systems, which are...
Play based sports monitoring techniques provide coaches and players with the tools to better measure the effects of training or live performance. This paper explores the advantages of using accelerometers units, in an effort to better analyse over ground running in professional athletes. A large portion of studies in player monitoring in the Australian Football League (AFL) utilize GPS to obtain time...
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