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Proof Fixing a > λ 1 and taking c as the main bifurcation parameter, we can obtain a supercritical bifurcating branch of positive solutions to (1.1), which emanates from the semi-trivial solution ( θ a, 0 ) at the value of c ˜ = λ 1 ( − d ( 1 − e − γ θ a ) ).
The parameter (Iin[I_{0},I_{1}]subset mathbf{R}) is the main bifurcation parameter and is often associated with the injected current in a real neuron.
In this article, we choose λ as a main bifurcation parameter and consider the complicated dynamic behavior near the fixed point E 1 with the effect of diffusion.
In this article, we take λ as a main bifurcation parameter, study stability of the constant positive equilibrium E 1, which exists for λ ∈ ( 0, λ ¯ ).
The main bifurcation parameter is given by I, the magnitude of the current step protocol, and leads to the following classical definition of excitability via bifurcation analysis under the variation of the applied current I [4]: Type I: The stable equilibrium (resting state) disappears via a saddle-node on invariant circle (SNIC) bifurcation.
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Hence, it makes sense to consider the coefficients ((a,c)) in the normal form as the main bifurcation parameters.
In this section, by discussing the bifurcations of positive solutions by using a and c as the main bifurcation parameters, respectively, we establish the multiplicity of positive solutions when γ is suitably large.
The two two-parameter bifurcation diagrams share the same primary bifurcation parameter (the primary differentiation signal, S1) on the horizontal axis.
Bifurcation parameter I (A) or z (B).
In addition, the Hopf bifurcation is a type codimension-one bifurcation, that is, the bifurcation results by one bifurcation parameter.
Let c 22 be the bifurcation parameter.
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