Face detection is an intelligent approach used in a variety of applications that identifies human faces digital images. This work presents new method which composes neural network and Techebycheve transforms for face detection. For feature extraction, Tchebychev transform was applied, discrete given different sampling patterns several samples here were performed on color A Levenberg-Marquardt b...

Taking a new choice of the LM parameter ? k = ? J T F ? with id="M2"> ? open="(" close="]" 0,2 , we give modified Levenb...

A well-organized scheduling method is needed to meet the time-varying power necessities. The distribution of in forthcoming days must be scheduled. system's accuracy extensively impinges on economic function and reliability. At peak load time, detaching procedure necessary for decreasing demand load. This complexity conquered by present system forecasting centered constraints which affect Predi...

We present an approach based on the improved Levenberg Marquardt (LM) algorithm of backpropagation (BP) neural network to estimate the light source position in bioluminescent imaging. For solving the forward problem, the table-based random sampling algorithm (TBRS), a fast Monte Carlo simulation method we developed before, is employed here. Result shows that BP is an effective method to positio...

Matthew Tomes,1 Florian Marquardt,2,3 Gaurav Bahl,1 and Tal Carmon1,* 1Department of Electrical Engineering, University of Michigan, Ann Arbor, Michigan 48109, USA 2Institut für Theoretische Physik, Universität Erlangen-Nürnberg, Staudtstrasse 7, D-91058 Erlangen, Germany 3Max Planck Institute for the Science of Light, Günther-Scharowsky-Strasse 1/Bau 24, D-91058 Erlangen, Germany (Received 16 ...

We consider a regularized Levenberg–Marquardt method for solving nonlinear ill-posed inverse problems. We use the discrepancy principle to terminate the iteration. Under certain conditions, we prove the convergence of the method and obtain the order optimal convergence rates when the exact solution satisfies suitable source-wise representations. Mathematics Subject Classification (2000) 65J15 ·...

Max Ludwig, ∗ Amir H. Safavi-Naeini, Oskar Painter, and Florian Marquardt 3 Institute for Theoretical Physics, Universität Erlangen-Nürnberg, Staudtstr. 7, 91058 Erlangen, Germany Thomas J. Watson, Sr, Laboratory of Applied Physics, California Institute of Technology, Pasadena, California 91125, USA. Max Planck Institute for the Science of Light, Günther-Scharowsky-Straße 1/Bau 24, 91058 Erlang...

We extend the theory of Sobolev gradients to include variable metric methods, such as Newton’s method and the Levenberg-Marquardt method, as gradient descent iterations associated with stepwise variable inner products. In particular, we obtain existence, uniqueness, and asymptotic convergence results for a gradient flow based on a variable inner product.