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The constraint function can be described as Open image in new window Fig. 6 Red dots denote the control points of beam and shell varvec{u}_{a}^{C} = varvec{u}_{a}^{S}, (19 where the superscript C and S denote the displacement of the ath point of beam curve and surface respectively.

Inspired by least absolute shrinkage and selection operator (LASSO) algorithm [8], an ℓ1-norm sparse constraint function can be used to take the advantage of channel sparsity in adaptive sparse channel estimation (ASCE); zero-attracting ISS-NLMS (ZA-ISS-NLMS) has been proposed for ASCE [9, 10] to improve the estimation performance.

We show that with this end-point constraint the optimized cost function can be seen as a Lyapunov function for the system and can thus be used to prove stability.

These general constraints, like the cost function, can be modified and adapted as dictated by the needs of the project.

It is found that in this low-frequency limit, constraints on the flame transfer function can be established from global conservation laws for mass, energy, and momentum.

Descent directions for the dual function can be constructed from the constraint slacks associated with the Lagrangian maximizers.

Thus, the elasticity of the constraints and the flexibility of the target values in the objective function can be quantified.

Inequality constraints with aggregate functions can be used to enforce other resource restrictions, like CPU load, bandwidth use, or maximum number of running components.

By considering the stress-free states of the plate, a constraint condition on the growth functions can be derived.

Therefore, membership functions for the fuzzy total cost function and constraints can be figured out, from which the optimal fuzzy basic period and cycle times can be determined in addition to the compromised crisp values in fuzzy sense.

If the filters have high vanishing moments in total, the variable number of objective function and constraints can be reduced.