Tudoret F, Bardou A, Carrault G
Laboratoire Traitement du Signal et de l'Image, INSERM 99-34, Université de Rennes 1, France.
Acta Biotheor. 2001;49(4):247-60. doi: 10.1023/a:1014218308856.
Much research effort has been directed in different physiological contexts towards describing realistic behaviors with differential equations. One observes obviously that more state-variables give the model more accuracy. Unfortunately, the computational cost involved is higher. A new algorithm is presented for simulating a model described by a system of differential equations in which efficiency may not be altered by its size. In order to do this, the method is based on a polynomial description of the state-variables' evolution and on a computation distributed control. Evaluations and results performed with classical models like Fitzhugh Nagumo or Hodgkin Huxley, allow validation of the method and exhibits its potential to decrease the computational costs.
在不同的生理环境下，人们投入了大量的研究精力，试图用微分方程来描述现实行为。显然可以观察到，更多的状态变量会使模型更精确。不幸的是，所涉及的计算成本更高。本文提出了一种新算法，用于模拟由微分方程组描述的模型，该模型的效率不会因其规模而改变。为了实现这一点，该方法基于状态变量演化的多项式描述和计算分布式控制。使用诸如Fitzhugh Nagumo或Hodgkin Huxley等经典模型进行的评估和结果，验证了该方法，并展示了其降低计算成本的潜力。
