Hindmarsh rose model with delay (dde)

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SUMMARY

The discussion centers on utilizing the MATLAB dde23 solver for the Hindmarsh rose model with delay. The equations presented include dx/dt, dy/dt, and dz/dt, which incorporate delay terms. Key solutions for setting history values for the delay include using x(t) = x(0) for all t<0, x(t) = 0 for t<0, or employing the undelayed ODE approach for t-tau. The dde23 solver is confirmed to be suitable for this problem, alongside the alternative of using Simon Wood's solv95 program.

PREREQUISITES
  • Understanding of MATLAB programming and syntax
  • Familiarity with delay differential equations (DDEs)
  • Knowledge of the Hindmarsh rose model dynamics
  • Basic concepts of initial value problems in differential equations
NEXT STEPS
  • Explore MATLAB's dde23 documentation for detailed usage
  • Research alternative methods for solving DDEs, such as the method of steps
  • Investigate Simon Wood's solv95 program for DDE solutions
  • Study the implications of history values in delay differential equations
USEFUL FOR

Mathematicians, researchers in computational biology, and engineers working with dynamic systems that involve delay differential equations.

kaledh
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hi all,

I have a problem using the MATLAB dde23 solver to evaluate the delayed HR model:


dx/dt = y(t) - a*x(t)^3 + b*x(t)^2 - z(t) + e (x(t-tau) - x(t))

dy/dt = c - d*x(t)^2 - y(t)

dz/dt = r [ s*(x(t) - xo) - z(t)]


how could I set the history values (-tau<t<0)?

it is possible use the dde23 solver or I must use some approximation? if so what's the best approximation method?

please help me.
tnx
 
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kaledh said:
hi all,

I have a problem using the MATLAB dde23 solver to evaluate the delayed HR model:

dx/dt = y(t) - a*x(t)^3 + b*x(t)^2 - z(t) + e (x(t-tau) - x(t))
dy/dt = c - d*x(t)^2 - y(t)
dz/dt = r [ s*(x(t) - xo) - z(t)]

how could I set the history values (-tau<t<0)?

it is possible use the dde23 solver or I must use some approximation? if so what's the best approximation method?

please help me.
tnx

Hi,

I should have thought that the simplest thing to do would be just to put x(t) = x(0) for all t<0. An alternative would be x(t)=0 for t<0: this would imply that the delayed variable simply 'doesn't exist' before t=tau. Finally, you could put x(t-tau)=x(t)for t<0: this is tantamount to solving the undelayed ODE up to t-tau, and putting the delay in for t>tau. You could always experiment.

That said, most of the DDEs I have worked with have come out integrating a PDE w.r.t. its 'non-time' variable (e.g. Gurney WSC, Nisbet RM, Lawton, JH. 1983. The systematic formulation of tractable single-species population models incorporating age structure. Journal of Animal Ecology 52: 479-495.) and so the history of the delayed variable comes out naturally. Maybe just putting t-tau for t in the right-hand side of an ODE is not a good way of getting a DDE without extra thought.

The dde23 solve in Matlab should also work with this problem. There is also Simon Wood's solv95 programme (http://www.maths.bath.ac.uk/~sw283/simon/dde.html ).

Ashley
 
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