Time Shifts to Reduce the Size of Reservoir Computers
Thomas L. Carroll, Joseph D. Hart

TL;DR
This paper introduces a method to reduce the complexity of reservoir computers by using time-shifted output signals, enabling high performance with fewer nonlinear nodes and faster operation.
Contribution
The authors propose a novel time-shifting technique that simplifies reservoir computer design by decreasing the number of nonlinear nodes needed for effective computation.
Findings
High performance achieved with fewer nonlinear nodes
Delay-based reservoir computers operate at higher speeds
Time-shifting increases reservoir memory and rank
Abstract
A reservoir computer is a type of dynamical system arranged to do computation. Typically, a reservoir computer is constructed by connecting a large number of nonlinear nodes in a network that includes recurrent connections. In order to achieve accurate results, the reservoir usually contains hundreds to thousands of nodes. This high dimensionality makes it difficult to analyze the reservoir computer using tools from dynamical systems theory. Additionally, the need to create and connect large numbers of nonlinear nodes makes it difficult to design and build analog reservoir computers that can be faster and consume less power than digital reservoir computers. We demonstrate here that a reservoir computer may be divided into two parts; a small set of nonlinear nodes (the reservoir), and a separate set of time-shifted reservoir output signals. The time-shifted output signals serve to…
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Taxonomy
TopicsNeural Networks and Reservoir Computing · Advanced Memory and Neural Computing · Optical Network Technologies
