The frequency equations, mode shape and force vector are formulated in terms of the elements of the structural matrices.
The measurement model of field angle and direction vectors is formulated by processing satellite image of Mars obtained from optical camera.
The problem of finding the weight vectors is formulated as an eigenvector problem with a unique solution.
A robust Capon beamformer (RCB) against the uncertainty of nominal array steering vector (ASV) is formulated in this paper.
Also, a non-parametric characterization of the search space at each iteration using a framework based on support vector machine is formulated.
The i-vector extraction is formulated in probabilistic terms based on a latent variable model as in (2), similarly for the case of i-supervector in (6).
The lth displacement vector △x l is formulated as △x l =(r cos(θ l ),r sin(θ l )), where (theta _{l}=frac {360^{o}}{L}l) and r is the scale parameter (i.e., the distance from the neighboring pixels to the focused pixel) of WLTP.
The design of the weight vector of the estimator is formulated as a constrained optimization problem.
As an extended version of support vector machine (SVM), SVR is formulated for the case of regression while SVM is usually used for classification and recognition.
In order to address the particular problem setup, a multilevel vector-optimization programming problem is formulated, which is tackled by a proposed novel Artificial Intelligence (AI -based decentrAI -basedolutionary optimization algorithm.
