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→The solution: parmeter -> parameter |
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The (non-negative) damping factor λ is adjusted at each iteration. If reduction of S is rapid a smaller value can be used bringing the algorithm closer to the GNA, whereas if an iteration gives insufficient reduction in the residual λ can be increased giving a step closer to the gradient descent direction. A similar damping factor appears in [[Tikhonov regularization]], which is used to solve linear ill-posed problems.
If a retrieved step length or the reduction of sum of squares to the latest parameter vector '''p''' fall short to
== External links ==
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