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Neuromorphic crossbar circuit with nanoscale filamentary-switching binary memristors for speech recognition

2014; Springer Science+Business Media; Volume: 9; Issue: 1 Linguagem: Inglês

10.1186/1556-276x-9-629

1931-7573

Son Ngoc Truong, Seok-Jin Ham, Kyeong‐Sik Min,

Neuroscience and Neural Engineering

Abstract In this paper, a neuromorphic crossbar circuit with binary memristors is proposed for speech recognition. The binary memristors which are based on filamentary-switching mechanism can be found more popularly and are easy to be fabricated than analog memristors that are rare in materials and need a more complicated fabrication process. Thus, we develop a neuromorphic crossbar circuit using filamentary-switching binary memristors not using interface-switching analog memristors. The proposed binary memristor crossbar can recognize five vowels with 4-bit 64 input channels. The proposed crossbar is tested by 2,500 speech samples and verified to be able to recognize 89.2% of the tested samples. From the statistical simulation, the recognition rate of the binary memristor crossbar is estimated to be degraded very little from 89.2% to 80%, though the percentage variation in memristance is increased very much from 0% to 15%. In contrast, the analog memristor crossbar loses its recognition rate significantly from 96% to 9% for the same percentage variation in memristance.