<span lang="EN-US">In this paper, a new method is developed to model the wind speed data that considered as function of seasonal variations. A hybrid artificial neural network (HANN) investigated based on Weibull distribution model. The presented HANN predicts with and chronological characteristics similar real data. design farm was implemented using MATLAB software. suggested has been ap...

We review the integration between the genetic and evolutionary techniques with artificial neural networks. A Lamarckian model is proposed based on genetic algorithms and artificial neural networks. The genetic algorithm evolves the population while the artificial neural network performs the learning process. The direct encoding scheme was used. This model was submitted to several data sets and ...

The improved computation presented in this paper is aimed to optimize the neural networks learning process using Levenberg-Marquardt (LM) algorithm. Quasi-Hessian matrix and gradient vector are computed directly, without Jacobian matrix multiplication and storage. The memory limitation problem for LM training is solved. Considering the symmetry of quasi-Hessian matrix, only elements in its uppe...

Abstract In this article, we analyze the convergence rate of modified Levenberg-Marquardt (MLM) method under Hölderian local error bound condition and continuity Jacobian, which are more general than Lipschitz Jacobian. Under special circumstances, MLM coincides with results presented by Fan. A globally convergent algorithm trust region technique will also be given.

We present an iterative multiresolution algorithm for the translational and rotational alignment of digital images. An image is represented by an interpolating spline. Coarser versions of this continuous image model are obtained by using spline approximations at various scales (polynomial spline pyramid). We use a coarse-to-fine updating strategy to compute the alignment parameters iteratively,...

To actively maneuver a robotic capsule for interactive diagnosis in the gastrointestinal tract, visualizing accurate position and orientation of the capsule when it moves in the gastrointestinal tract is essential. A possible method that encloses the circuits, batteries, imaging device, etc into the capsule looped by an axially magnetized permanent-magnet ring is proposed. Based on expression o...

Traditional learning algorithms with gradient descent based technique, such as back-propagation (BP) and its variant Levenberg-Marquardt (LM) have been widely used in the training of multilayer feedforward neural networks. The gradient descent based algorithm may converge usually slower than required time in training, since many iterative learning step are needed by such learning algorithm, and...

This paper applied a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) learning algorithm capable to estimate parameters and states of highly nonlinear unknown plant in noisy environment. The proposed KFRNN identifier, learned by the Backpropagation and L-M learning algorithm, was incorporated in a direct and indirect adaptive neural control s...

Simultaneous Localization and Mapping (SLAM) has focused on noisy but unique data associations resulting in linear Gaussian uncertainty models. However, a unique decision is often not possible using only local information, giving rise to ambiguities that have to be resolved globally during optimization. To solve this problem, the pose graph data structure is extended here by multimodal constrai...