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Generally, an engineering problem can be modeled by partial differential equations (PDEs).
Realizing that the distributed power control (PC) problem can be modeled by a timed game between a given transmitter and its environment, the authors wanted to know whether this approach can be applied to distributed PC.
In centralized case, the cross-layer design problem can be modeled by constrained Markov decision process (CMDP) and solved by a dynamic programming method to achieve the optimal performance.
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Therefore, many real world problems can be modeled by stochastic differential equations.
It is known that many physically significant problems can be modeled by initial value problems of the form x ′ ( t ) + A x ( t ) = 0, x ( 0 ) = x 0, (1.1).
It is well known (see [1]) that many physically significant problems can be modeled by the initial-value problems of the form.
Interestingly, we also find that some scene labeling problems can be modeled by tree convex constraints in a natural and meaningful way.
It is well known that many physically significant problems can be modeled by initial value problems of the following form: (x'(t)+Ax t)=0), (x 0)=x_{0}) where A is an accretive operator in an appropriate Banach space.
It is well known that many physically significant problems can be modeled by initial value problems (IVP) of the following form: x ′ ( t ) + A x ( t ) = 0, x ( 0 ) = x 0, (1.1).
It is well known that many physically significant problems can be modeled by initial value problems of the form x ′ ( t ) + A x ( t ) = 0, x ( 0 ) = x 0, (1.2).
The non-autonomous phenomenon is so prevalent in the real life that many epidemiological problems can be modeled by non-autonomous systems of nonlinear differential equations [8 11], which should be more realistic than autonomous differential equations.
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