نتایج جستجو برای: hessian matrix

تعداد نتایج: 366902  

2002
Tomas McKelvey

A new minimal parametrization of multivariable linear system is proposed. The parametrization is defined as a perturbation around the realization of a nominal transfer function. A particular parameter basis is selected which, for the impulse response identification problem, leads to a Hessian matrix of the criterion function which is equal to the identity matrix.

2011
YoungSuk Bang Hany S. Abdel-Khalik

When nonlinear behavior must be considered in sensitivity analysis studies, one needs to approximate higher order derivatives of the response of interest with respect to all input data. This paper presents an application of a general reduced order method to constructing higher order derivatives of response of interest with respect to all input data. In particular, we apply the method to constru...

2015
GERARD AWANOU

We prove a convergence result for a mixed finite element method for the Monge-Ampère equation to its weak solution in the sense of Aleksandrov. The unknowns in the formulation are the scalar variable and the Hessian matrix.

1999
Margaret H. Wright

Certain matrix relationships play an important role in optimality conditions and algorithms for nonlinear and semideenite programming. Let H be an n n symmetric matrix, A an m n matrix, and Z a basis for the null space of A. (In the context of optimization, H is the Hessian of a smooth function and A is the Jacobian of a set of constraints.) When the reduced Hessian Z T HZ is positive deenite, ...

Journal: :The Journal of chemical physics 2013
Bongsoo Kim Fumio Hirata

A new statistical mechanics formulation of characterizing the structural fluctuation of protein correlated with that of water is presented based on the generalized Langevin equation and the 3D-reference interaction site model (RISM)/RISM theory of molecular liquids. The displacement vector of atom positions, and their conjugated momentum, are chosen for the dynamic variables for protein, while ...

Journal: :IEEE Trans. Automat. Contr. 2000
James C. Spall

Stochastic approximation (SA) has long been applied for problems of minimizing loss functions or root finding with noisy input information. As with all stochastic search algorithms, there are adjustable algorithm coefficients that must be specified, and that can have a profound effect on algorithm performance. It is known that choosing these coefficients according to an SA analog of the determi...

2010
T. Balakumaran I. L. A. Vennila C. Gowri Shankar

Mammography is a widely used diagnostic technique for early breast cancer detection in women. Clusters of Microcalcification are the sign of breast cancer and their detection will decrease the probability of mortality rate and improves its prognosis. The detection of microcalcification clusters is a difficult task for radiologists because of variations of size and orientation and are highly cor...

Journal: :Pattern Recognition 2003
Fabio Sartori Edwin R. Hancock

In this paper we describe a new shape-from-shading method. We show how the parallel transport of surface normals can be used to impose curvature consistency and also to iteratively update surface normal directions so as to improve the brightness error. We commence by showing how to make local estimates of the Hessian matrix from surface normal information. With the local Hessian matrix to hand,...

Journal: :Math. Program. 1974
Philip E. Gill Walter Murray

This paper describes two numerically stable methods for unconstrained optimization and their generalization when linear inequality constraints are added. The difference between the two methods is simply that one requires the Hessian matrix explicitly and the other does not. The methods are intimately based on the recurrence of matrix factorizations and are linked to earlier work on quasi-Newton...

1997
V. Jeyakumar

In this paper, we present generalizations of the Jacobian matrix and the Hessian matrix to continuous maps and continuously diierentiable functions respectively. We then establish second-order optimality conditions for mathematical programming problems with continuously dif-ferentiable functions. The results also sharpen the corresponding results for problems involving C 1;1-functions.

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