Reservoir computing was achieved by constructing a network of virtual nodes multiplexed in time and sharing a single silicon beam exhibiting a classical Duffing non-linearity as the source of nonlinearity. The delay-coupled electromechanical system performed well on time series classification tasks, with error rates below 0.1% for the 1st, 2nd, and 3rd order parity benchmarks and an accuracy of ( 78 ± 2 ) % for the TI-46 spoken word recognition benchmark. As a first demonstration of reservoir computing using a non-linear mass-spring system in MEMS, this result paves the way to the creation of a new class of compact devices combining the functions of sensing and computing.Reservoir computing was achieved by constructing a network of virtual nodes multiplexed in time and sharing a single silicon beam exhibiting a classical Duffing non-linearity as the source of nonlinearity. The delay-coupled electromechanical system performed well on time series classification tasks, with error rates below 0.1% for the 1st, 2nd, and 3rd order parity benchmarks and an accuracy of ( 78 ± 2 ) % for the TI-46 spoken word recognition benchmark. As a first demonstration of reservoir computing using a non-linear mass-spring system in MEMS, this result paves the way to the creation of a new class of compact devices combining the functions of sensing and computing.
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Reservoir computing with a single delay-coupled non-linear mechanical oscillator
Semantic Scholar · Engineering · 2018
Abstract
Reservoir computing was achieved by constructing a network of virtual nodes multiplexed in time and sharing a single silicon beam exhibiting a classical Duffing non-linearity as the source of nonlinearity. The delay-coupled electromechanical system performed well on time series classification tasks, with error rates below 0.1% for the 1st, 2nd, and 3rd order parity benchmarks and an accuracy of ( 78 ± 2 ) % for the TI-46 spoken word recognition benchmark. As a first demonstration of reservoir computing using a non-linear mass-spring system in MEMS, this result paves the way to the creation of a new class of compact devices combining the functions of sensing and computing.Reservoir computing was achieved by constructing a network of virtual nodes multiplexed in time and sharing a single silicon beam exhibiting a classical Duffing non-linearity as the source of nonlinearity. The delay-coupled electromechanical system performed well on time series classification tasks, with error rates below 0.1% for the 1st, 2nd, and 3rd order parity benchmarks and an accuracy of ( 78 ± 2 ) % for the TI-46 spoken word recognition benchmark. As a first demonstration of reservoir computing using a non-linear mass-spring system in MEMS, this result paves the way to the creation of a new class of compact devices combining the functions of sensing and computing.
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