The Human Operator Model: a Comparison of Parameter Optimization Methods |
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0.2 Starting point 15.6612 Convergence Achieved A-matrix approximated assumed C. W. Merriam calculated comparison computation conjugate gradient method criterion cubic interpolation Davidon Fletcher Powell descent and conjugate design function DFP method direction vector E₂ efficient equations 12 equations 24 error function evaluation Figure Fletcher Powell Method flowchart Footnotes to Chapter Function Difference An+1 Function Iteration Trials function-gradient point-evaluations Gauss elimination Hessian HUMAN OPERATOR MODEL inner product inverse Iteration Trials Value linearly independent matrix Method Conjugate Gradient Newton Raphson method Newton Raphson procedure non-quadratic one-dimensional minimization positive definite Powell and Steepest quadratic convergence quadratic function Raphson and Conjugate search direction second order method Square Root Decomposition starting guess Starting Point 2,5 Starting Point 5,20 steepest descent method symmetric symmetric matrix Theorem Trajectory Trials Value x1 Value x1 X2 X₁ x1 X2 Function X2 Function Difference Δ Δ δχ ε₁ хо