New binary memristor crossbar architecture based neural networks for speech recognition

In this paper, we propose a new binary memristor crossbar architecture based neural networks for speech recognition. The circuit can recognize five vowels. The proposed crossbar is tested by 1,000 speech samples and recognized 94% of the tested samples. We use Monte Carlo simulation to estimate recognitition rate. The percentage variation in memristance is increased from 0% to 15%, the recognition rate is degraded from 94% to 82%.
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