Sentence examples for minimization problem to from inspiring English sources
Regularization penalties are introduced to the corresponding minimization problem to promote sparsity in PC loadings.
For example, maximization of noisy autoencoder accuracy almost gives grid cells, but some elusive ingredient is still missing from the minimization problem to yield grid cells like those experimentally observed.
By integrating the regularization term into the standard back-projection framework, we solve a least squares minimization problem to seek the desired high-resolution (HR) image.
This is called the chord version of the SONET ADMs minimization problem, to denote the fact that the routing is not given a priori.
We then define a probabilistic semantics for the costs, and prove the equivalence of the cost minimization problem to the Bayesian network MAP (maximum a posteriori probability) solution of the system.
We focus on the decoupling principal and it is shown that the observer can be designed independently via a norm minimization problem to reduce effects of disturbances and model mismatch.
Performance-based optimality criteria incorporating performance indices are proposed, and can be used in any continuum topology optimization methods for compliance minimization problems to obtain the optimum.
Using the matrix perturbation theory and the equivalent modified equation approach for finite difference methods, we propose a class of minimization problems to optimize the free-parameters in the MRT-LBM.
The proposed design is formulated into a power-minimization problem to guarantee the IRs' information and ERs' energy requirements while avoiding the information being intercepted by Eves.
According to the theory of compressive sensing, when α is sparse enough, it is feasible to solve the related convex ℓ 1-minimization problem to avoid solving the solution of ℓ 0-minimization problem directly: (7) α ^ 1 = arg min α 1 subject to y = X α.
The cone complementary algorithm is employed to design H∞ controllers based on a solution to a nonlinear minimization problem subject to a set of linear matrix inequalities.
