Quasi-Newton methods have played a prominent role, over many years, in the design of effective practical methods for the numerical solution of nonlinear minimization problems and in multi-dimensional zero-finding. There is a wide literature outlining the properties of these methods and illustrating their performance [e.g., [8]]. In addition, most modern optimization libraries house a quasi-Newt...

A new family of limited-memory variationally-derived variable metric or quasi-Newton methods for unconstrained minimization is given. The methods have quadratic termination property and use updates, invariant under linear transformations. Some encouraging numerical experience is reported.

In this paper, a space-time absolute nodal coordinate formulation cable (SAC) element forming technique based on the Lagrange family of shape functions is proposed. Two distinct SAC elements, each with spatial function, have been generated by method. Moreover, external forces such as bending moment and air resistance formula accounted for. The multiplier method, along concepts replacement const...

In this paper, we consider block-decomposition first-order methods for solving large-scale conic semidefinite programming problems given in standard form. Several ingredients are introduced to speedup the method in its pure form such as: an aggressive choice of stepsize for performing the extragradient step; use of scaled inner products; dynamic update of the scaled inner product for properly b...

It is well known that the conjugate gradient method and a quasi-Newton method, using any well-defined update matrix from the one-parameter Broyden family of updates, produce the same iterates on a quadratic problem with positive-definite Hessian. This equivalence does not hold for any quasi-Newton method. We discuss more precisely the conditions on the update matrix that give rise to this behav...

A physics-based multicell electrothermal equivalent circuit model is described that is applied to the large-signal microwave characterization of AlGaAs/GaAs HBT’s. This highly efficient model, which incorporates a new multifinger electrothermal model, has been used to perform dc, small-signal and loadpull characterization, and investigate parameter-spreads due to fabrication process variations....

This paper presents Artificial Neural Network (ANN) implementation for the Radio Frequency (RF) and Mechanical modeling of lateral RF Micro Electro Mechanical System (MEMS) series micro machined Single pole double through (SPDT) switch. We propose an efficient approach based on ANN for analyzing the losses in ON and OFF state of lateral RF MEMS series switch by calculating the S-parameters. The...