English

Spoken digit classification using a spin-wave delay-line active-ring reservoir computing

Neural and Evolutionary Computing 2020-05-27 v1 Disordered Systems and Neural Networks

Abstract

As a test of general applicability, we use the recently proposed spin-wave delay line active-ring reservoir computer to perform the spoken digit recognition task. On this, classification accuracies of up to 93% are achieved. The tested device prototype employs improved spin wave transducers (antennas). Therefore, in addition, we also let the computer complete the short-term memory (STM) task and the parity check (PC) tasks, because the fading memory and nonlinearity are essential to reservoir computing performance. The resulting STM and PC capacities reach maximum values of 4.77 and 1.47 respectively.

Keywords

Cite

@article{arxiv.2005.12557,
  title  = {Spoken digit classification using a spin-wave delay-line active-ring reservoir computing},
  author = {Stuart Watt and Mikhail Kostylev},
  journal= {arXiv preprint arXiv:2005.12557},
  year   = {2020}
}

Comments

12 pages, 3 figures

R2 v1 2026-06-23T15:48:44.953Z