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Neuronal activities including calcium sodium current, ligands current, and synaptic transmembrane current create electromagnetic fields. Here, an analytic method is suggested to obtain the electromagnetic fields and potential signals resulting from the function of nerve cells inside the brain. Modeling simulates the behavior of cells three‐dimensionally. The proposed method employs the electric scalar...
Deep neural networks are gaining in popularity as they are used to generate state-of-the-art results for a variety of computer vision and machine learning applications. At the same time, these networks have grown in depth and complexity in order to solve harder problems. Given the limitations in power budgets dedicated to these networks, the importance of low-power, low-memory solutions has been stressed...
We present a novel dynamic configuration technique for deep neural networks that permits step-wise energy-accuracy tradeoffs during runtime. Our configuration technique adjusts the number of channels in the network dynamically depending on response time, power, and accuracy targets. To enable this dynamic configuration technique, we co-design a new training algorithm, where the network is incrementally...
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