Synchronized transform-limited operation of 10-GHz colliding pulse mode-locked laser

We report a 10-GHz colliding pulse mode-locked laser fabricated with integrated active-passive waveguides. The laser fabrication adopted a deep reactive ion etching and single-step metal-organic vapor phase epitaxy regrowth process for forming the buried heterostructure waveguide. Clean output pulses resulted from laterally tilting the active-passive interface and effectively suppressing residual back-reflections at the interface. Hybrid mode-locking resulted in a synchronized transform-limited sech/sup 2/optical waveform. Pulsewidth, chirp, timing jitter, and frequency-locking range were investigated through systematic device biasing condition optimization.     

Hybrid Subset Simulation method for reliability estimation of dynamical systems subject to stochastic excitation

A hybrid Subset Simulation approach is proposed for reliability estimation for general dynamical systems subject to stochastic excitation. This new stochastic simulation approach combines the advantages of the two previously proposed Subset Simulation methods, Subset Simulation with Markov Chain Monte Carlo (MCMC) algorithm and Subset Simulation with splitting. The new method employs the MCMC algorithm before reaching an intermediate failure level and splitting after reaching the level to exploit the causality of dynamical systems. The statistical properties of the failure probability estimators are derived. Two examples are presented to demonstrate the effectiveness of the new approach and to compare with the previous two Subset Simulation methods. The results show that the new method is robust to the choice of proposal distribution for the MCMC algorithm and to the intermediate failure events selected for Subset Simulation.     

Image reconstruction of a buried perfectly conducting cylinder illuminated by transverse electric waves

This article presents a computational approach to the image reconstruction of a perfectly conducting cylinder illuminated by transverse electric waves. A perfectly conducting cylinder of unknown shape buried in one half‐space and scatters the incident wave from another half‐space where the scattered field is recorded. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived, and the imaging problem is reformulated into an optimization problem. The steady state genetic algorithm is then employed to find out the global extreme solution of the cost function. Numerical results demonstrated that, even when the initial guess is far away from the exact one, good reconstruction can be obtained. In such a case, the gradient‐based methods often get trapped in a local extreme. In addition, the effect of different noise on the reconstruction is investigated. © 2006 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 15, 261–265, 2005     

Neural networks based subgrid scale modeling in large eddy simulations

In this paper a multilayer feed-forward neural network (NN) is used as subgrid scale (SGS) model in a large eddy simulation (LES). The NN was previously off-line trained using numerical data generated by a LES of a channel flow at Re_τ=180 with Bardina's scale similar (BFR) SGS model. Results show the ability of NNs to identify and reproduce the highly nonlinear behavior of the turbulent flows, and therefore the possibility of using NN techniques in numerical simulations of turbulent flows.     

An efficient posture recognition method using fuzzy logic

Computer-human interaction plays an important role in virtual reality. Glove-based input devices have many desirable features which make direct interactions between the user and the virtual world possible. However, due to the complexity of the human hand, recognising hand functions precisely and efficiently is not an easy task. Existing algorithms are either imprecise or computationally expensive, making them impractical to integrate with VR applications, which are usually very CPU intensive.In the problem of posture and gesture recognition, both the sample patterns stored in the database and the ones to be recognised may be imprecise. This kind of imprecise knowledge can be best dealt with using fuzzy logic. A fast and simple posture recognition method using fuzzy logic is presented in this paper. Our model consists of three components: the posture database, the classifier and the identifier. The classifier roughly classifies the sample postures before they are put into the posture database. The identifier compares an input posture with the records in the identified class and finds the right match efficiently. Fuzzy logic is applied in both the classification and identification processes to cope with imprecise data. The main goal of this method is to recognise hand functions in an accurate and efficient manner. The accuracy, efficiency and the noise tolerance of the model have been examined through a number of experiments.     

Multi-Scale Spoken Document Retrieval for Cantonese Broadcast News

This paper presents the application of a multi-scale paradigm to Chinese spoken document retrieval (SDR) for improving retrieval performance. Multi-scale refers to the use of both words and subwords for retrieval. Words are basic units in a language that carry lexical meaning, and subword units (such as phonemes, syllables or characters) are building components for words. Retrieval using subword indexing units is better than retrieval using words because of the robustness of subword units to out-of-vocabulary (OOV) words during speech recognition and ambiguities in word segmentation. Experimental results have demonstrated that subword bigrams can bring improvement in retrieval performance over words (～9.56%). Application of multi-scale fusion to SDR aims at combining the lexical information of words and the robustness of subwords. This work presents the first detailed investigation for a Cantonese broadcast news retrieval task using two different multi-scale fusion approaches: pre-retrieval fusion and post-retrieval fusion. Multi-scale retrieval using both words and syllable bigrams achieves improvement in retrieval performance (～1.90%) over retrieval on the composite scales.     

Performance comparison between the training method and the numerical method of the orthogonal neural network in function approximation

The orthogonal neural network is a recently developed neural network based on the properties of orthogonal functions. It can avoid the drawbacks of traditional feedforward neural networks such as initial values of weights, number of processing elements, and slow convergence speed. Nevertheless, it needs many processing elements if a small training error is desired. Therefore, numerous data sets are required to train the orthogonal neural network. In the article, a least‐squares method is proposed to determine the exact weights by applying limited data sets. By using the Lagrange interpolation method, the desired data sets required to solve for the exact weights can be calculated. An experiment in approximating typical continuous and discrete functions is given. The Chebyshev polynomial is chosen to generate the processing elements of the orthogonal neural network. The experimental results show that the numerical method in determining the weights gives as good performance in approximation error as the known training method and the former has less convergence time. © 2004 Wiley Periodicals, Inc. Int J Int Syst 19: 1257–1275, 2004.     

Formation of subwavelength grating on molybdenum mirrors using a femtosecond Ti:sapphire laser system operating at 10 Hz

We report formation of subwavelength surface grating over large surface area of molybdenum mirror by multiple irradiation of amplified femtosecond laser pulses from a homemade Ti:sapphire oscillator-amplifier laser system in a raster scan configuration. The laser system delivered 2 mJ, 80 fs duration laser pulses at a pulse repetition rate of 10 Hz. Various parameters such as pulse fluence, number of pulses, laser polarization, scan speed, and scan steps were optimized to obtain uniform subwavelength gratings. Energy dispersive x-ray spectroscopy measurements were conducted to analyze the elemental composition of mirror surfaces before and after laser treatment.     

Optical diagnostics of mercury jet for an intense proton target

An optical diagnostic system is designed and constructed for imaging a free mercury jet interacting with a high intensity proton beam in a pulsed high-field solenoid magnet. The optical imaging system employs a backilluminated, laser shadow photography technique. Object illumination and image capture are transmitted through radiation-hard multimode optical fibers and flexible coherent imaging fibers. A retroreflected illumination design allows the entire passive imaging system to fit inside the bore of the solenoid magnet. A sequence of synchronized short laser light pulses are used to freeze the transient events, and the images are recorded by several high speed charge coupled devices. Quantitative and qualitative data analysis using image processing based on probability approach is described. The characteristics of free mercury jet as a high power target for beam-jet interaction at various levels of the magnetic induction field is reported in this paper.     

Robust CMAC control schemes for dynamic trajectory following

Abstract

Improved robust CMAC control schemes are proposed for tracing dynamic trajectories in this paper. There are two main structures in the proposed control schemes: one is the robust controller and the other is the improved CMAC network. The robust controller technique can achieve a certain goal without concern for instability of the controlled system in the presence of significant plant uncertainties if the nominal parameter is roughly estimated. Next, in order to reduce the tracing error, a suitable nominal parameter needs to be chosen. Thus, the improved CMAC learning approach under the robust control structure, using the concept of credit assignment, will be employed to determine control variables that can trace other states repeatedly during control processes. Finally, simulation results demonstrate the capability of the proposed control schemes to trace dynamic trajectories.