Gaussian etched single transverse mode vertical-cavity surface-emitting laser

A continuous Gaussian profile matched to the fundamental mode was etched onto the aperture of a vertical cavity surface emitting laser (VCSEL). Single Gaussian spot emission was achieved over the entire operating current range.

10-Gbit/s transmission over 300-m standard multimode fiber using multilevel coding and 2-channel WDM

A combination of multilevel coding schemes and simple two-channel wavelength division multiplexing (WDM) at 1300 and 1550 nm was used to transmit an aggregate of 10 Gbit/s over 300 m of multimode fiber that is typical of that employed in current Local Area Networks (LANs). It was shown that this technique could be a simple solution for achieving 10 Gigabit ethernet links over installed multimode fiber building backbones.

Short-channel polymer field-effect-transistor fabrication using spin-coating-induced edge template and ink-jet printing

A method to fabricate polymer field-effect transistors with submicron channel lengths is described. A thin polymer film is spin coated on a prepatterned resist with a low resolution to create a thickness contrast in the overcoated polymer layer. After plasma and solvent etching, a submicron-sized line structure, which templates the contour of the prepattern, is obtained. A further lift-off process is applied to define source-drain electrodes of transistors. With a combination of ink-jet printing, transistors with channel length down to 400 nm have been fabricated by this method. We show that drive current density increases as expected, while the on/off current ratio 106 is achieved. © 2005 American Institute of Physics.

Gaussian process change point models

We combine Bayesian online change point detection with Gaussian processes to create a nonparametric time series model which can handle change points. The model can be used to locate change points in an online manner; and, unlike other Bayesian online change point detection algorithms, is applicable when temporal correlations in a regime are expected. We show three variations on how to apply Gaussian processes in the change point context, each with their own advantages. We present methods to reduce the computational burden of these models and demonstrate it on several real world data sets. Copyright 2010 by the author(s)/owner(s).

Gaussian mixture modeling with Gaussian process latent variable models

Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristics of the data. Recently, the Gaussian Process Latent Variable Model (GPLVM) has successfully been used to find low dimensional manifolds in a variety of complex data. The GPLVM consists of a set of points in a low dimensional latent space, and a stochastic map to the observed space. We show how it can be interpreted as a density model in the observed space. However, the GPLVM is not trained as a density model and therefore yields bad density estimates. We propose a new training strategy and obtain improved generalisation performance and better density estimates in comparative evaluations on several benchmark data sets. © 2010 Springer-Verlag.

Gaussian Process Regression Networks

We introduce a new regression framework, Gaussian process regression networks (GPRN), which combines the structural properties of Bayesian neural networks with the non-parametric flexibility of Gaussian processes. This model accommodates input dependent signal and noise correlations between multiple response variables, input dependent length-scales and amplitudes, and heavy-tailed predictive distributions. We derive both efficient Markov chain Monte Carlo and variational Bayes inference procedures for this model. We apply GPRN as a multiple output regression and multivariate volatility model, demonstrating substantially improved performance over eight popular multiple output (multi-task) Gaussian process models and three multivariate volatility models on benchmark datasets, including a 1000 dimensional gene expression dataset.

High mobility N-channel and P-channel nanocrystalline silicon thin-film transistors

We report high hole and electron mobilities in nanocrystalline silicon (nc-Si:H) top-gate staggered thin-film transistors (TFTs) fabricated by direct plasma-enhanced chemical vapor deposition (PECVD) at 260°C. The n-channel nc-Si:H TFT with n+ nc-Si:H ohmic contacts shows a field-effect electron mobility (μnFE) of 130 cm2/Vs, which increases to 150 cm2/Vs with Cr-silicide contacts, along with a field-effect hole mobility (μhFE) of 25 cm2/Vs. To the best of our knowledge, the hole and electron mobilities reported here are the highest achieved to date using direct PECVD. © 2005 IEEE.