extremum


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extremum

[ek′strēm·əm]
(mathematics)
A maximum or minimum value of a function. Also known as extreme.
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.
References in periodicals archive ?
As only extremum points are essential, the dispersion due to an element size is not a significant problem.
Bratcu, "MPPT for grid-connected photovoltaic systems using ripple-based Extremum Seeking Control: Analysis and control design issues," Solar Energy, vol.
Combining with the symmetry, it reaches the extremum when q = 1/2.
By substituting the system parameters shown in Table 3, the two extremum values [b.sub.min] and [b.sub.max] can be determined.
This vector field-based navigation algorithm only takes advantage of a pathfinder when the agent gets trapped at a local extremum. That is, the pathfinder is only used near a local extremum when there is a need to escape from it.
In view of the basic thought of TV/PSO-GRNN in Figure 2, the extremum output response [Y.sub.i, max]([x.sub.i]) of all dynamic response [Y.sub.i] (t, [x.sub.i]) corresponding with the i-th input random vector x, is obtained through a number of stochastic analyses within the time domain [0, T].
Concerning the objective functional in (1), it is possible to find an optimal distribution of the hybrid optional effectiveness functions starting with the functional (1) extremum existence conditions of (2) and (3).
To eliminate the effects of different dimensions, units, and orders of magnitude among indices, the matrix R should be normalized by the extremum method.
The so-called optimization involves finding the extremum of the target function in the solution space.
Online methods are the extremum seeking control (ESC) method, ripple correlation control (RCC) method, hill climbing (HC) method [10], incremental conductance (IC) method, and perturbation and observation (P&O) method [11] and modified P&O [12,13].
In the solution space, each paritcle's position and velocity are updated by the individual extremum [P.sub.best] and the population extremum [G.sub.best], where [P.sub.best] and [G.sub.best] are updated by comparing the fitness value of the new particle.
Therefore, in order to improve the generalization capability of the ELM, in the process of updating the individual extremum locations and population extremum locations, both the fitness values of the particles and also the output matrix norm of the ELM network are considered.