Related Experiment Video
Updated: Jul 7, 2026

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
Published on: March 10, 2011
Identification of a specific limitation on local-feedback recurrent networks acting as Mealy-Moore machines
1Guelph Natural Computation Research Group, Computing and Information Science Department, University of Guelph, Guelph, Ontario, N1G 2W1, Canada.
Abstract:
This paper describes a proof which identifies limitations of local-feedback recurrent networks (LFRN's) in representing Mealy-Moore machines. Specifically, it identifies a class of machines that are unrepresentable in these networks. While it is known that LFRN's cannot represent all automata, this is the first paper to show a specific class of unrepresentable automata. The paper goes beyond previous work in the area by addressing realistic activation functions, arbitrary network architectures, and more general computing machines.
Related Concept Videos
Woodward–Hoffmann Selection Rules and Microscopic Reversibility
Root Loci for Positive-Feedback Systems
The construction rules for the root locus in positive feedback systems are similar to those in...
Sequence Networks of Rotating Machines
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
Simplified Synchronous Machine Model
In this model, each generator is connected to a...
Positive and Negative Feedback Loops
Multi-input and Multi-variable systems
In the absence of...
