In tackling the problem of minimizing the deformation of a loaded structure, by varying the shape of the original structure, past second order optimization efforts have focused on general Newton techniques like the Davidon-Fletcher-Powell (DFP) update formula and the BroydenFletcher-Goldfarb-Shanno (BFGS) formula which iteratively build estimates of the structure's Hessian. This thesis bypasses...

We consider the problem of solving linear systems of equations with limited-memory members of the restricted Broyden class and symmetric rank-one matrices. In this paper, we present various methods for solving these linear systems, and propose a new approach based on a practical implementation of the compact representation for the inverse of these limited-memory matrices. Using the proposed app...

This paper examines the performance of time of arrival (TOA) estimation techniques for an UWB system employing a non-coherent energy collection receiver. The performance of two different algorithms, namely, the threshold-crossing (TC) and the maximum selection (MAX) algorithms, are compared in terms of TOA estimation error. The effect of the TOA estimation error on position calculation is evalu...

Conjugate gradient methods are efficient for smooth optimization problems, while there are rare conjugate gradient based methods for solving a possibly nondifferentiable convex minimization problem. In this paper by making full use of inherent properties of Moreau-Yosida regularization and descent property of modified conjugate gradient method we propose a modified Fletcher-Reeves-type method f...

Epileptic seizures correspond to episodes of increased rhythmicity of the normally chaotic activity in biological neural networks. We propose to use hybrid neural networks where artificial neural networks are used to control the biological neural networks by learning their different states. The learning is dramatically accelerated when using a conjugate gradient method in conjunction with the F...

<p>This paper presents an innovative approach in finding optimal solution of multimodal and multivariable function for global optimization problems that involve complex inefficient second derivatives. Artificial bees colony (ABC) algorithm possessed good exploration search, but the major weakness at its exploitation stage. The proposed algorithms improved ABC by hybridized with most effec...

The periodic generalized harmonic wavelet (PGHW) method is used to analyze the response of chain-like multi-degree-of-freedom (MDOF) nonlinear structural system with seismic excitation in time and frequency domain. First, theoretical background PGHW briefly introduced, relationship between power spectral density (PSD) stochastic process corresponding coefficient given. Next, wavelet-Galerkin st...

In matrix analysis, the scaling technique reduces chances of an ill-conditioning matrix. This article proposes a one-parameter memoryless Davidon–Fletcher–Powell (DFP) algorithm for solving system monotone nonlinear equations with convex constraints. The measure function that involves all eigenvalues DFP is minimized to obtain parameter’s optimal value. resulting and derivative-free low memory ...

This paper examines the efficiency of various methods of calibrating a rainfall-runoff model. The model used is a 12 parameter version of the Bough ton model which has been developed for large tropical basins. Attempts were made to improve the efficiency of calibration in three areas: selection of the best nonlinear programming algorithms; reduction of the number of objective functions required...

This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulpi...