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In the jump problem on the type change line for Lavrent'ev-Bitsadze equation, we need to seek a function which.
Otherwise, if n is an odd number, we seek a function x on ([-n+1,n+1]).
We can write u = P + u + P − u for u ∈ E. Now, we are going to seek a function u in E such that A 1 u = g ( x, t, u ).
We will seek a function μ ¯ ( t ) such that the right hand side of (18) is nonnegative for 0 < r < 1 and t > 0. Since u 0 ( r ) and u 0 ′ ( r ) are bounded in [ 0, 1 ], we can choose μ ¯ ( 0 ), such that v ¯ ( r, 0 ) = ω ( r, μ ¯ ( 0 ) ) ≥ u 0 ( r ).
In other words, we seek a function f such that q TF=f [TF]).
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(4.3) For disturbed data (f^{delta}(t)), we use the Tikhonov regularization method, which seeks a function (v^{delta}_{alpha} x,cdot)) from minimizing quadratic functional J_{alpha}bigl v^{delta}bigr):={biglVert Kv^{delta}-f^{delta}bigrVert }^{2}+{ alpha}^{2}{biglVert v^{delta}bigrVert }^{2}.
The right seeks a functioning marketplace in health care, subsidized but not micromanaged by the government.
Here we show that these reachability questions can be addressed through an "altitude function" analysis, in which we seek a scalar function of the system state that permits conclusions to be made regarding reachability without computing system trajectories.
In Appendix Two we develop an "altitude function" approach to this reachability problem, in which we seek a scalar function of the system state that permits conclusions to be made regarding reachability without computing system trajectories.
In functional PCA, we seek a sequence of orthonormal functions, ψ j (t ), that take the role of PCs but for functional data.
Then, as now, theorists and practitioners of intelligence sought a smoothly functioning, highly efficient and seamlessly integrated organization, or cluster of organizations.
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