scholarly journals Vector Difference Equations, Substochastic Matrices, and Design of Multi-networks to Reduce the Spread of Epidemics

Author(s):  
Harold M. Hastings ◽  
Tai Young-Taft
2004 ◽  
Vol 2004 (7) ◽  
pp. 603-611 ◽  
Author(s):  
Rigoberto Medina ◽  
M. I. Gil'

The paper deals with the vector discrete dynamical systemxk+1=Akxk+fk(xk). Thewell-known result by Perron states that this system is asymptotically stable ifAk≡A=constis stable andfk(x)≡f˜(x)=o(‖x‖). Perron's result gives no information about the size of the region of asymptotic stability and norms of solutions. In this paper, accurate estimates for the norms of solutions are derived. They give us stability conditions for (1.1) and bounds for the region of attraction of the stationary solution. Our approach is based on the “freezing” method for difference equations and on recent estimates for the powers of a constant matrix. We also discuss applications of our main result to partial reaction-diffusion difference equations.


2003 ◽  
Vol 2003 (48) ◽  
pp. 3059-3066
Author(s):  
Rigoberto Medina

Accurate estimates for the norms of the solutions of a vector difference equation are derived. They give us stability conditions and bounds for the region of attraction of the stationary solution. Our approach is based on estimates for the powers of a constant matrix. We also discuss applications of our main results to partial reaction-diffusion difference equations and to a Volterra difference equation.


1995 ◽  
Vol 32 (4) ◽  
pp. 851-866 ◽  
Author(s):  
Paul Glasserman ◽  
David D. Yao

We give a unified presentation of stability results for stochastic vector difference equations based on various choices of binary operations and , assuming that are stationary and ergodic. In the scalar case, under standard addition and multiplication, the key condition for stability is E[log |A0|] < 0. In the generalizations, the condition takes the form γ< 0, where γis the limit of a subadditive process associated with . Under this and mild additional conditions, the process has a unique finite stationary distribution to which it converges from all initial conditions.The variants of standard matrix algebra we consider replace the operations + and × with (max, +), (max,×), (min, +), or (min,×). In each case, the appropriate stability condition parallels that for the standard recursions, involving certain subadditive limits. Since these limits are difficult to evaluate, we provide bounds, thus giving alternative, computable conditions for stability.


1995 ◽  
Vol 32 (04) ◽  
pp. 851-866 ◽  
Author(s):  
Paul Glasserman ◽  
David D. Yao

We give a unified presentation of stability results for stochastic vector difference equations based on various choices of binary operations and , assuming that are stationary and ergodic. In the scalar case, under standard addition and multiplication, the key condition for stability is E [log |A 0|] &lt; 0. In the generalizations, the condition takes the form γ&lt; 0, where γis the limit of a subadditive process associated with . Under this and mild additional conditions, the process has a unique finite stationary distribution to which it converges from all initial conditions. The variants of standard matrix algebra we consider replace the operations + and × with (max, +), (max,×), (min, +), or (min,×). In each case, the appropriate stability condition parallels that for the standard recursions, involving certain subadditive limits. Since these limits are difficult to evaluate, we provide bounds, thus giving alternative, computable conditions for stability.


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