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where A l k = ∂ A l / ∂ x k, which is supplemented by the normalization condition ∑ k Z k ( t ) d x k ∗ / d t = ω.
which is holomorphic on K m − 1 ∖ { P ∞ } with a pole of order 2 at P ∞, and the constants { z j } j = 1, …, m − 1 are determined by the normalization condition.
Moreover, the firing rate in the stationary state N is determined by the normalization condition (2.3), or equivalently, a ( N ) N = ∫ − ∞ V F [ e − ( v − V 0 ( N ) ) 2 2 a ( N ) ∫ max ( v, V R ) V F e ( w − V 0 ( N ) ) 2 2 a ( N ) d w ] d v. (3.3).
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By using the normalization condition for stationary distribution, we have.
The normalization condition is given by Q 0, 0 + ∑ j = 0 1 ∑ n = 1 L Q n, j = 1.
The normalization condition is given by ∑ j = 0 1 ∑ n = 0 L − 1 P n, j + P L, 0 = 1.
Therefore, the steady state probability vector can be represented as π=(π 1,π 2,...,π D ) and the normalization condition is given by (sum limits _{d} {{boldsymbol {pi }_{d}}} = 1).
When the system is in the steady or equilibrium state, the normalization condition is given by (sum limits _{i = 0}^{N} {sum limits _{j = 0}^{N} {{boldsymbol {pi _{ textit {i,j})}} = 1} }}) [49] with the condition that 0≤i≤N, 0≤j≤N, and 0≤i+j≤N.
By using the (smoothing) Fischer-Burmeister NCP function and the normalization condition eTx = 1, the Pareto eigenvalue problem can be converted into a equivalent semismooth (or smoothing) system of equations, where e = (1, … , 1)T.
enforcing the normalization condition.
(1) Calculate the weights: (6) enforcing the normalization condition.
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