The nonlinear conjugate gradient method is a very useful technique for solving large scale minimization problems and has wide applications in many fields. In this paper, we present a new algorithm of ...

Abstract: Fuzzy system of linear equations (FSLE) comes from many fields, including mathematics, physics, engineering and so on. It is an interesting work to study numerical methods solving the system ...

Abstract: A stochastic conjugate gradient algorithm (SCGA) is proposed for the solving of the nonlinear optimization problem associated with the multiuser constant modulus algorithm (CC-CMA) for ...

This is a PyTorch based machine learning project that focuses on implementing the Trust Region Newton Conjugate Gradient (TRNCG) optimization algorithm to train a neural network. Since TRNCG is not ...

In this paper, we presented a new three-term conjugate gradient method based on combining the conjugate gradient method proposed by Cheng et al [15] with the idea of the modified FR method [22]. In ...

There are several optimization techniques available in PROC NLMIXED. You can choose a particular optimizer with the TECH=name option in the PROC NLMIXED statement. No algorithm for optimizing general ...