Add to ORKG288 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.We show experimental results in applying Novel to solve nonlinear optimisation problems, including (a) the learning of feedforward neural networks, (b) the design of quadrature-mirror-filter digital filter banks, (c) the satisfiability problem, (d) the maximum satisfiability problem, and (e) the design of multiplierless quadrature-mirror-filter digital filter banks. Our method achieves better solutions than existing methods, or achieves solutions of the same quality but at a lower cost.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD
Constrained nonlinear optimization problems are usually solved using penalty or barrier methods com...
This article provides a condensed overview of some of the major today's features (both classical or ...
a b s t r a c t A novel method of locating all real roots of systems of nonlinear equations is prese...
288 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.We show experimental results ...
... these new methods, we develop a prototype, called Novel (Nonlinear Optimization Via External Lea...
In this thesis we present new methods for solving nonlinear optimization problems These problems a...
We propose a neural network approach for global optimization with applications to nonlinear least sq...
We propose a neural network approach for global optimization with applications to nonlinear least sq...
In this paper, we present a new global-search method for designing QMF (quadrature-mirror- lter) lte...
[[abstract]]This paper proposes a zero-order method of nonlinear optimization using back-propagation...
In this thesis, we present new methods for solving nonlinear optimization problems. These problems a...
In this thesis, a new global optimization technique, its applications in particular to neural networ...
Optimization plays a significant role in almost every field of applied sciences (e.g., signal proces...
The gradient search fails in an optimization problem where the objective function is not differentia...
Abstract—This paper presents a new method that inte-grates tabu search, simulated annealing, genetic...
Constrained nonlinear optimization problems are usually solved using penalty or barrier methods com...
This article provides a condensed overview of some of the major today's features (both classical or ...
a b s t r a c t A novel method of locating all real roots of systems of nonlinear equations is prese...
288 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.We show experimental results ...
... these new methods, we develop a prototype, called Novel (Nonlinear Optimization Via External Lea...
In this thesis we present new methods for solving nonlinear optimization problems These problems a...
We propose a neural network approach for global optimization with applications to nonlinear least sq...
We propose a neural network approach for global optimization with applications to nonlinear least sq...
In this paper, we present a new global-search method for designing QMF (quadrature-mirror- lter) lte...
[[abstract]]This paper proposes a zero-order method of nonlinear optimization using back-propagation...
In this thesis, we present new methods for solving nonlinear optimization problems. These problems a...
In this thesis, a new global optimization technique, its applications in particular to neural networ...
Optimization plays a significant role in almost every field of applied sciences (e.g., signal proces...
The gradient search fails in an optimization problem where the objective function is not differentia...
Abstract—This paper presents a new method that inte-grates tabu search, simulated annealing, genetic...
Constrained nonlinear optimization problems are usually solved using penalty or barrier methods com...
This article provides a condensed overview of some of the major today's features (both classical or ...
a b s t r a c t A novel method of locating all real roots of systems of nonlinear equations is prese...