Optimum Integration Procedure For Connectionist And Dynamic Field Equations

FRONTIERS IN NEUROROBOTICS(2021)

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摘要
Connectionist and dynamic field models consist of a set of coupled first-order differential equations describing the evolution in time of different units. We compare three numerical methods for the integration of these equations: the Euler method, and two methods we have developed and present here: a modified version of the fourth-order Runge Kutta method, and one semi-analytical method. We apply them to solve a well-known nonlinear connectionist model of retrieval in single-digit multiplication, and show that, in many regimes, the semi-analytical and modified Runge Kutta methods outperform the Euler method, in some regimes by more than three orders of magnitude. Given the outstanding difference in execution time of the methods, and that the EM is widely used, we conclude that the researchers in the field can greatly benefit from our analysis and developed methods.
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关键词
cognitive neuroscience, connectionism and neural nets, neurorobotic, cognitive models, numerical optimisation techniques
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