Proposal for a novel and simple WDM NRZ-DPSK system

A novel and simple non-return-to-zero differential phase shift keying (NRZ-DPSK) wavelength division multiplexing (WDM) system, which can simultaneously demultiplex and demodulate multiple wavelengths, is proposed and investigated in this paper. The phase-to-intensity demodulation principle is based on detuned filtering, which is achieved by using a single commercial array waveguide grating (AWG) in our scheme. By properly choosing appropriate AWG channels at the transmitter, the AWG at the receiver can act as both the demultiplexer and the demodulator of the DPSK signals. Simulations at 10, 20, and 40 Gbit/s show good flexibility and performance for the proposed system. © 2009 Higher Education Press and Springer-Verlag GmbH.

A critical analysis of loudness calculation methods

The physical meaning and calculation procedures for determining loudness was critically analyzed. Four noise sources were used in comparing the software packages dBFA dBSonic, which were used in the investigation to a public domain code. The purpose of the comparison was to evaluate the validity of the results obtained and to gain an idea of the shortcomings of the relevant standards. A comparison of the results for loudness was computed from various methods, used in the study. Two basic sources of input data such as a sound level meter (SLM) and a 01 dB data acquisition system (DAQ), were available for the comparison. The SLM directly gave 1/3 octave band levels, while the data from the DAQ was filtered to give the results. Five processing methods, including a Visual Basic (VB) program and a VB program adapted from dBFA, were used for the study. It was found that the calculation of loudness from 1/3 octave cannot be separated from the filtering process.

Estimating labels from label proportions

Consider the following problem: given sets of unlabeled observations, each set with known label proportions, predict the labels of another set of observations, also with known label proportions. This problem appears in areas like e-commerce, spam filtering and improper content detection. We present consistent estimators which can reconstruct the correct labels with high probability in a uniform convergence sense. Experiments show that our method works well in practice. Copyright 2008 by the author(s)/owner(s).

A Hierarchical Model for Ordinal Matrix Factorization

This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based on Gibbs sampling and one based on variational Bayes. Importantly, these algorithms may be implemented in the factorization of very large matrices with missing entries. The model is evaluated on a collaborative filtering task, where users have rated a collection of movies and the system is asked to predict their ratings for other movies. The Netflix data set is used for evaluation, which consists of around 100 million ratings. Using root mean-squared error (RMSE) as an evaluation metric, results show that the suggested model outperforms alternative factorization techniques. Results also show how Gibbs sampling outperforms variational Bayes on this task, despite the large number of ratings and model parameters. Matlab implementations of the proposed algorithms are available from cogsys.imm.dtu.dk/ordinalmatrixfactorization.

Improved bounds for subband-adaptive iterative shrinkage/thresholding algorithms.

This paper presents new methods for computing the step sizes of the subband-adaptive iterative shrinkage-thresholding algorithms proposed by Bayram & Selesnick and Vonesch & Unser. The method yields tighter wavelet-domain bounds of the system matrix, thus leading to improved convergence speeds. It is directly applicable to non-redundant wavelet bases, and we also adapt it for cases of redundant frames. It turns out that the simplest and most intuitive setting for the step sizes that ignores subband aliasing is often satisfactory in practice. We show that our methods can be used to advantage with reweighted least squares penalty functions as well as L1 penalties. We emphasize that the algorithms presented here are suitable for performing inverse filtering on very large datasets, including 3D data, since inversions are applied only to diagonal matrices and fast transforms are used to achieve all matrix-vector products.

Multi scale shape index for 3D object recognition

We present Multi Scale Shape Index (MSSI), a novel feature for 3D object recognition. Inspired by the scale space filtering theory and Shape Index measure proposed by Koenderink & Van Doorn [6], this feature associates different forms of shape, such as umbilics, saddle regions, parabolic regions to a real valued index. This association is useful for representing an object based on its constituent shape forms. We derive closed form scale space equations which computes a characteristic scale at each 3D point in a point cloud without an explicit mesh structure. This characteristic scale is then used to estimate the Shape Index. We quantitatively evaluate the robustness and repeatability of the MSSI feature for varying object scales and changing point cloud density. We also quantify the performance of MSSI for object category recognition on a publicly available dataset. © 2013 Springer-Verlag.

Rao-Blackwellized particle smoothers for mixed linear/nonlinear state-space models

We consider the smoothing problem for a class of conditionally linear Gaussian state-space (CLGSS) models, referred to as mixed linear/nonlinear models. In contrast to the better studied hierarchical CLGSS models, these allow for an intricate cross dependence between the linear and the nonlinear parts of the state vector. We derive a Rao-Blackwellized particle smoother (RBPS) for this model class by exploiting its tractable substructure. The smoother is of the forward filtering/backward simulation type. A key feature of the proposed method is that, unlike existing RBPS for this model class, the linear part of the state vector is marginalized out in both the forward direction and in the backward direction. © 2013 IEEE.

Instantaneous frequency and bandwidth estimation using filterbank arrays

Accurate estimation of the instantaneous frequency of speech resonances is a hard problem mainly due to phase discontinuities in the speech signal associated with excitation instants. We review a variety of approaches for enhanced frequency and bandwidth estimation in the time-domain and propose a new cognitively motivated approach using filterbank arrays. We show that by filtering speech resonances using filters of different center frequency, bandwidth and shape, the ambiguity in instantaneous frequency estimation associated with amplitude envelope minima and phase discontinuities can be significantly reduced. The novel estimators are shown to perform well on synthetic speech signals with frequency and bandwidth micro-modulations (i.e., modulations within a pitch period), as well as on real speech signals. Filterbank arrays, when applied to frequency and bandwidth modulation index estimation, are shown to reduce the estimation error variance by 85% and 70% respectively. © 2013 IEEE.

On-chip switching of a silicon nitride micro-ring resonator based on digital microfluidics platform.

We demonstrate the switching of a silicon nitride micro ring resonator (MRR) by using digital microfluidics (DMF). Our platform allows driving micro-droplets on-chip, providing control over the effective refractive index at the vicinity of the resonator and thus facilitating the manipulation of the transmission spectrum of the MRR. The device is fabricated using a process that is compatible with high-throughput silicon fabrication techniques with buried highly doped silicon electrodes. This platform can be extended towards controlling arrays of micro optical devices using minute amounts of liquid droplets. Such an integration of DMF and optical resonators on chip can be used in variety of applications, ranging from biosensing and kinetics to tunable filtering on chip.

Chirp-enhanced direct modulation of a monolithic sub-Terahertz dual laser transmitter

A technique enabling 10 Gbps data to be directly modulated onto a monolithic sub-THz dual laser transmitter is proposed. As a result of the laser chirp, the logical zeros of the resultant sub-THz signal have a different peak frequency from that of the logical ones. The signal extinction ratio is therefore enhanced by suppressing the logical zeros with a filter stage at the receiver. With the aid of the chirp-enhanced filtering, an improved extinction ratio can be achieved at moderate modulation current. Hence, 10 GHz modulation bandwidth of the transmitter is predicted without the need for external modulators. In this paper, we demonstrate the operational principle by generating an error-free (bit error rate less than 10-9) 100 Mbps Manchester encoded signal with a centre frequency of 12 GHz within the bandwidth of an envelope detector, whilst direct modulation of a 100 GHz signal at data rates of up to 10 Gbps is simulated by using a transmission line model. This work could be a key technique for enabling monolithic sub-THz transmitters to be readily used in high speed wireless links. © 2013 IEEE.

A flame surface density approach to large-eddy simulation of premixed turbulent combustion

The flame surface density approach to the modeling of premixed turbulent combustion is well established in the context of Reynolds-averaged simulations. For the future, it is necessary to consider large-eddy simulation (LES), which is likely to offer major advantages in terms of physical accuracy, particularly for unsteady combustion problems. LES relies on spatial filtering for the removal of unresolved phenomena whose characteristic length scales are smaller than the computational grid scale. Thus, there is a need for soundly based physical modeling at the subgrid scales. The aim of this paper is to explore the usefulness of the flame surface density concept as a basis for LES modeling of premixed turbulent combustion. A transport equation for the filtered flame surface density is presented, and models are proposed for unclosed terms. Comparison with Reynolds-averaged modeling is shown to reveal some interesting similarities and differences. These were exploited together with known physics and statistical results from experiment and from direct numerical stimulation in order to gain insight and refine the modeling. The model has been implemented in a combustion LES code together with standard models for scalar and momentum transport. Computational results were obtained for a simple three-dimensional flame propagation test problem, and the relative importance of contributing terms in the modeled equation for flame surface density was assessed. Straining and curvature are shown to have a major influence at both the resolved and subgrid levels.