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Competition Aided with Continuous-Time Nonlinear Model

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Book cover Competition-Based Neural Networks with Robotic Applications

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSAPPLSCIENCES))

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Abstract

In this chapter, different from the model presented in Chap. 1, we present a continuous-time dynamic model, which is described by an ordinary differential equation and is able to produce the winner-take-all competition by taking advantage of selective positive-negative feedback. The global convergence is proven analytically and the convergence rate is also discussed. Simulations are conducted in the static competition and the dynamic competition scenarios. Both theoretical and numerical results validate the effectiveness of the dynamic equation in describing the nonlinear phenomena of winner-take-all competition.

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Authors and Affiliations

  1. The Hong Kong Polytechnic University, Hong Kong, China

    Shuai Li

  2. Lanzhou University, Lanzhou, China

    Long Jin

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  1. Shuai Li
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  2. Long Jin
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Correspondence to Shuai Li .

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Li, S., Jin, L. (2018). Competition Aided with Continuous-Time Nonlinear Model. In: Competition-Based Neural Networks with Robotic Applications. SpringerBriefs in Applied Sciences and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-10-4947-7_2

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  • DOI: https://doi.org/10.1007/978-981-10-4947-7_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4946-0

  • Online ISBN: 978-981-10-4947-7

  • eBook Packages: EngineeringEngineering (R0)

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