The BFGS method is one of the most famous quasi-Newton algorithms for unconstrained optimization. In 1984, Powell presented an example of a function of two variables that shows that the Polak–Ribière–Polyak (PRP) conjugate gradient method and the BFGS quasi-Newton method may cycle around eight nonstationary points if each line search picks a local minimum that provides a reduction in the object...

We present a simple extension of standard Bussgang blind equalization algo rithms that signi cantly improves their convergence properties Our technique uses the inverse channel estimate to lter the regressor signal The modi ed algorithms provide quasi Newton convergence in the vicinity of a local minimum of the chosen cost function with only a modest increase in the overall computational comple...

Optimizations of atomic positions belong to the most commonly performed tasks in electronic structure calculations. Many simulations like global minimum searches or characterizations of chemical reactions require performing hundreds or thousands of minimizations or saddle computations. To automatize these tasks, optimization algorithms must not only be efficient but also very reliable. Unfortun...

Problem statement: The Maximum Likelihood Estimation (MLE) technique is the most efficient statistical approach to estimate parameters in a cross-sectional model. Often, MLE gives rise to a set of non-linear systems of equations that need to be solved iteratively using the Newton-Raphson technique. However, in some situations such as in the Negative-Lindley distribution where it involves more t...

We discuss herein filtering problems involving the emulation of nonlinear systems which have embedded dynamics and where the truth model consists only of an input and output sequence. It has been shown [1] that steepest descent training algorithms such as BackpropagationThrough-Time (BPTT) are locally H optimal for applications where training inputs vary at each weight update, or training epoch...

<p>The maximum power point tracking (MPPT) has been a popular terminology among those researchers who deal with one of the most available renewable energy resources called solar power. Many have evolved and proposed lot techniques for But each technique its pros cons. Some suffer from complexity as far implementation is concerned, whereas other lack accuracy. In current research work, it ...

A Lavrentiev type regularization technique for solving elliptic boundary control problems with pointwise state constraints is considered. The main concept behind this regularization is to look for controls in the range of the adjoint control-to-state mapping. After investigating the analysis of the method, a semismooth Newton method based on the optimality conditions is presented. The theoretic...