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A Note on Some Numerical Approaches to Solve a θ˙ Neuron Networks Model

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  • Samir Kumar Bhowmik
  • Feras M. Al Faqih
  • Md. Nazmul Islam

Abstract

Space time integration plays an important role in analyzing scientific and engineering models. In this paper, we consider an integrodifferential equation that comes from modeling θ˙ neuron networks. Here, we investigate various schemes for time discretization of a theta‐neuron model. We use collocation and midpoint quadrature formula for space integration and then apply various time integration schemes to get a full discrete system. We present some computational results to demonstrate the schemes.

Suggested Citation

  • Samir Kumar Bhowmik & Feras M. Al Faqih & Md. Nazmul Islam, 2014. "A Note on Some Numerical Approaches to Solve a θ˙ Neuron Networks Model," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:863842
    DOI: 10.1155/2014/863842
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    References listed on IDEAS

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    1. Changjin Xu & Peiluan Li, 2012. "Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling," Abstract and Applied Analysis, John Wiley & Sons, vol. 2012(1).
    2. Changjin Xu & Peiluan Li, 2012. "Dynamics in a Delayed Neural Network Model of Two Neurons with Inertial Coupling," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-17, August.
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    Cited by:

    1. Abdullah Aljouiee & Samir Kumar Bhowmik, 2015. "Windowed Fourier Frames to Approximate Two‐Point Boundary Value Problems," Abstract and Applied Analysis, John Wiley & Sons, vol. 2015(1).

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