Dynamics of on-line learning in radial basis function networks

On-line learning is examined for the radial basis function network, an important and practical type of neural network. The evolution of generalization error is calculated within a framework which allows the phenomena of the learning process, such as the specialization of the hidden units, to be analyzed. The distinct stages of training are elucidated, and the role of the learning rate described. The three most important stages of training, the symmetric phase, the symmetry-breaking phase, and the convergence phase, are analyzed in detail; the convergence phase analysis allows derivation of maximal and optimal learning rates. As well as finding the evolution of the mean system parameters, the variances of these parameters are derived and shown to be typically small. Finally, the analytic results are strongly confirmed by simulations.

Full-vectorial modeling of femtosecond pulses for laser inscription of photonic structures

During the last decade, microfabrication of photonic devices by means of intense femtosecond (fs) laser pulses has emerged as a novel technology. A common requirement for the production of these devices is that the refractive index modification pitch size should be smaller than the inscribing wavelength. This can be achieved by making use of the nonlinear propagation of intense fs laser pulses. Nonlinear propagation of intense fs laser pulses is an extremely complicated phenomenon featuring complex multiscale spatiotemporal dynamics of the laser pulses. We have utilized a principal approach based on finite difference time domain (FDTD) modeling of the full set of Maxwell's equations coupled to the conventional Drude model for generated plasma. Nonlinear effects are included, such as self-phase modulation and multiphoton absorption. Such an approach resolves most problems related to the inscription of subwavelength structures, when the paraxial approximation is not applicable to correctly describe the creation of and scattering on the structures. In a representative simulation of the inscription process, the signature of degenerate four wave mixing has been found. © 2012 Optical Society of America.

Design and analysis of a 2-DoF split-stator induction motor

A two degrees of freedom (2-DOF) actuator capable of producing linear translation, rotary motion, or helical motion would be a desirable asset to the fields of machine tools, robotics, and various apparatuses. In this paper, a novel 2-DOF split-stator induction motor was proposed and electromagnetic structure pa- rameters of the motor were designed and optimized. The feature of the direct-drive 2-DOF induction motor lies in its solid mover ar- rangement. In order to study the complex distribution of the eddy current field on the ferromagnetic cylinder mover and the motor’s operating characteristics, the mathematical model of the proposed motor was established, and characteristics of the motor were ana- lyzed by adopting the permeation depth method (PDM) and finite element method (FEM). The analytical and numerical results from motor simulation clearly show a correlation between the PDM and FEM models. This may be considered as a fair justification for the proposed machine and design tools.