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1997 | OriginalPaper | Buchkapitel

Local Analysis of Weakly Connected Maps

verfasst von : Frank C. Hoppensteadt, Eugene M. Izhikevich

Erschienen in: Weakly Connected Neural Networks

Verlag: Springer New York

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In previous chapters we studied dynamics of weakly connected networks governed by a system of ordinary differential equations. It is also feasible to consider weakly connected networks of difference equations, or mappings, of the form 1$$ X_i \mapsto F_i \left( {X_i ,\lambda } \right) + \varepsilon G_i \left( {X_i ,\lambda ,\rho ,\varepsilon } \right),{\text{ i = 1,}} \ldots {\text{,n, }}\varepsilon \ll {\text{1,}} $$ where the variables X i ∈ ℝm, the parameters λ ∈ Λ,ρ ∈ R and the functions F i and G i have the same meaning as in previous chapters. The weakly connected mapping (7.1) can be also written in the form $$ X_i^{k + 1} = F_i \left( {X_i^k ,\lambda } \right) + \varepsilon G_i \left( {X^k ,\lambda ,\rho ,\varepsilon } \right),{\text{ i = 1,}} \ldots {\text{,n, }}\varepsilon \ll {\text{1,}} $$ where X k is the kth iteration of the variable X. In this chapter we use form (7.1) unless we explicitly specify otherwise.

Metadaten
Titel
Local Analysis of Weakly Connected Maps
verfasst von
Frank C. Hoppensteadt
Eugene M. Izhikevich
Copyright-Jahr
1997
Verlag
Springer New York
DOI
https://doi.org/10.1007/978-1-4612-1828-9_7