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All phase-change neuromorphic device recognises correlations

By Anna Demming August 3, 2016

Traditional programmable computers are facing fundamental limitations in terms of speed and size, inspiring increasing interest in alternative paradigms such as neuromorphic computing. Researchers at IBM Research – Zurich and EPFL in Lausanne have now developed a spiking neural network computing architecture using phase-change memristors to mimic both the synapses and neurons in the neural system for the first time. They also demonstrate enhanced pattern and correlation distinguishing capabilities using a level-tuning mechanism similar to that found in the human auditory cortex.

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