Metamaterial filter for the near-visible spectrum

We demonstrate metamaterials operating in the near-visible regime based on two-dimensional arrays of gold-coated silicon nanopillars. The nanopillar arrays demonstrate a cutoff response at the metamaterial plasma frequency in accordance with theory and can be utilized for filtering applications. A plasma frequency in the near visible region of λ = 1 μm is calculated numerically for an array with a lattice constant of 300 nm and wire radius of 50 nm, with reflection measurements in agreement with numerical calculations. Such structures can be utilized for achieving negative-index based metamaterials for the visible spectrum. © 2012 American Institute of Physics.

Mixed source model and its adapted vocal tract filter estimate for voice transformation and synthesis

In current methods for voice transformation and speech synthesis, the vocal tract filter is usually assumed to be excited by a flat amplitude spectrum. In this article, we present a method using a mixed source model defined as a mixture of the Liljencrants-Fant (LF) model and Gaussian noise. Using the LF model, the base approach used in this presented work is therefore close to a vocoder using exogenous input like ARX-based methods or the Glottal Spectral Separation (GSS) method. Such approaches are therefore dedicated to voice processing promising an improved naturalness compared to generic signal models. To estimate the Vocal Tract Filter (VTF), using spectral division like in GSS, we show that a glottal source model can be used with any envelope estimation method conversely to ARX approach where a least square AR solution is used. We therefore derive a VTF estimate which takes into account the amplitude spectra of both deterministic and random components of the glottal source. The proposed mixed source model is controlled by a small set of intuitive and independent parameters. The relevance of this voice production model is evaluated, through listening tests, in the context of resynthesis, HMM-based speech synthesis, breathiness modification and pitch transposition. © 2012 Elsevier B.V. All rights reserved.

Metamaterial filter for the near-visible spectrum

We demonstrate metamaterials operating in the near-visible regime based on two-dimensional arrays of gold-coated silicon nanopillars. The nanopillar arrays demonstrate a cutoff response at the metamaterial plasma frequency in accordance with theory and can be utilized for filtering applications. A plasma frequency in the near visible region of λ = 1 μm is calculated numerically for an array with a lattice constant of 300 nm and wire radius of 50 nm, with reflection measurements in agreement with numerical calculations. Such structures can be utilized for achieving negative-index based metamaterials for the visible spectrum.

Design guidelines for granular particles in a conical centrifugal filter

Essential design criteria for successful drying of granular particles in a conical continuous centrifugal filter are developed in a dimensionless fashion. Four criteria are considered: minimum flow thickness (to ensure sliding bulk flow rather than particulate flow), desaturation position, output dryness and basket failure. The criteria are based on idealised physical models of the machine operation and are written explicitly as functions of the basket size lout, spin velocity Ω and input flow rate of powder Qp. The separation of sucrose crystals from liquid molasses is taken as a case study and the successful regime of potential operating points (lout, Ω) is plotted for a wide range of selected values of flow rate Qp. Analytical expressions are given for minimum and maximum values of the three independent parameters (lout, Ω, Qp) as a function of the slurry and basket properties. The viable operating regime for a conical centrifugal filter is thereby obtained as a function of the slurry and basket properties. © 2012 The Institution of Chemical Engineers.

Two problems with variational expectation maximisation for time-series models

Variational methods are a key component of the approximate inference and learning toolbox. These methods fill an important middle ground, retaining distributional information about uncertainty in latent variables, unlike maximum a posteriori methods (MAP), and yet generally requiring less computational time than Monte Carlo Markov Chain methods. In particular the variational Expectation Maximisation (vEM) and variational Bayes algorithms, both involving variational optimisation of a free-energy, are widely used in time-series modelling. Here, we investigate the success of vEM in simple probabilistic time-series models. First we consider the inference step of vEM, and show that a consequence of the well-known compactness property of variational inference is a failure to propagate uncertainty in time, thus limiting the usefulness of the retained distributional information. In particular, the uncertainty may appear to be smallest precisely when the approximation is poorest. Second, we consider parameter learning and analytically reveal systematic biases in the parameters found by vEM. Surprisingly, simpler variational approximations (such a mean-field) can lead to less bias than more complicated structured approximations.

Fast low-cost FIR filter processed ECDM labels for optical label switching

A code-label recognition time of less than 500ps is demonstrated using low-cost FIRfilters. The electronically-processed label provides a control signal from an auto-correlated label. Error-free electronic code-label switching of an optical 10Gb/s signal is demonstrated. © 2010 Optical Society of America.