Image deconvolution using a Gaussian scale mixtures model to approximate the wavelet sparseness constraint

This paper proposes to use an extended Gaussian Scale Mixtures (GSM) model instead of the conventional ℓ1 norm to approximate the sparseness constraint in the wavelet domain. We combine this new constraint with subband-dependent minimization to formulate an iterative algorithm on two shift-invariant wavelet transforms, the Shannon wavelet transform and dual-tree complex wavelet transform (DTCWT). This extented GSM model introduces spatially varying information into the deconvolution process and thus enables the algorithm to achieve better results with fewer iterations in our experiments. ©2009 IEEE.

Can frequency diversity provide performance gains for WSNs at 2.4GHz for the fire hydrant to above ground channel

Wireless Sensor Networks (WSNs) which utilise IEEE 802.15.4 technology offer the potential for low cost deployment and maintenance compared with conventional wired sensor networks, enabling effective and efficient condition monitoring of aged civil engineering infrastructure. We will address wireless propagation for a below to above ground scenario where one of the wireless nodes is located in a below ground fire hydrant chamber to permit monitoring of the local water distribution network. Frequency Diversity (FD) is one method that can be used to combat the damaging effects of multipath fading and so improve the reliability of radio links. However, no quantitative investigation concerning the potential performance gains from the use of FD at 2.4GHz is available for the outlined scenario. In this paper, we try to answer this question by performing accurate propagation measurements using modified and calibrated off-the-shelf 802.15.4 based sensor nodes. These measurement results are also compared with those obtained from simulations that employ our Modified 2D Finite-Difference Time-Domain (FDTD) approach. ©2009 IEEE.

High performance nanocomposite thin film transistors with bilayer carbon nanotube-polythiophene active channel by ink-jet printing

Nanocomposite thin film transistors (TFTs) based on nonpercolating networks of single-walled carbon nanotubes (CNTs) and polythiophene semiconductor [poly [5, 5′ -bis(3-dodecyl-2-thienyl)- 2, 2′ -bithiophene] (PQT-12)] thin film hosts are demonstrated by ink-jet printing. A systematic study on the effect of CNT loading on the transistor performance and channel morphology is conducted. With an appropriate loading of CNTs into the active channel, ink-jet printed composite transistors show an effective hole mobility of 0.23 cm 2 V-1 s-1, which is an enhancement of more than a factor of 7 over ink-jet printed pristine PQT-12 TFTs. In addition, these devices display reasonable on/off current ratio of 105-10 6, low off currents of the order of 10 pA, and a sharp subthreshold slope (<0.8 V dec-1). The work presented here furthers our understanding of the interaction between polythiophene polymers and nonpercolating CNTs, where the CNT density in the bilayer structure substantially influences the morphology and transistor performance of polythiophene. Therefore, optimized loading of ink-jet printed CNTs is crucial to achieve device performance enhancement. High performance ink-jet printed nanocomposite TFTs can present a promising alternative to organic TFTs in printed electronic applications, including displays, sensors, radio-frequency identification (RFID) tags, and disposable electronics. © 2009 American Institute of Physics.

Nanometer scale thermal drift of 4Gbit/s uncooled laser for tight-channel-spacing low-cost WDM

A 4Gbit/s directly modulated DBR laser is demonstrated with nanometre scale thermal tuning over an extended 20-70°C temperature range. >40dB side mode suppression over the entire temperature range is achieved. © 2005 Optical Society of America.

Relay node placement for wireless sensor networks deployed in tunnels

Node placement plays a significant role in the effective and successful deployment of Wireless Sensor Networks (WSNs), i.e., meeting design goals such as cost effectiveness, coverage, connectivity, lifetime and data latency. In this paper, we propose a new strategy to assist in the placement of Relay Nodes (RNs) for a WSN monitoring underground tunnel infrastructure. By applying for the first time an accurate empirical mean path loss propagation model along with a well fitted fading distribution model specifically defined for the tunnel environment, we address the RN placement problem with guaranteed levels of radio link performance. The simulation results show that the choice of appropriate path loss model and fading distribution model for a typical environment is vital in the determination of the number and the positions of RNs. Furthermore, we adapt a two-tier clustering multi-hop framework in which the first tier of the RN placement is modelled as the minimum set cover problem, and the second tier placement is solved using the search-and-find algorithm. The implementation of the proposed scheme is evaluated by simulation, and it lays the foundations for further work in WSN planning for underground tunnel applications. © 2010 IEEE.

Multi-channel signal separation

The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and cross-talk in data communications. In this paper, we propose iterative algorithms to solve the n × n linear time invariant system under two different constraints. Some existing solutions for 2 × 2 systems are reviewed and compared.

Efficient line launch for bandwidth improvement of 10 Gbit/s multimode fibre links using elliptical Gaussian beam

A novel elliptical Gaussian beam line launch is shown to allow improved system capacity for high speed multimode fibre links. This launch maintains higher bandwidth than dual launch even with misalignment of ±6 μm despite not requiring testing at installation. ©2010 IEEE.

Tractable nonparametric bayesian inference in poisson processes with Gaussian process intensities

The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian process is a useful way to place a prior distribution on this intensity. The combination of a Poisson process and GP is known as a Gaussian Cox process, or doubly-stochastic Poisson process. Likelihood-based inference in these models requires an intractable integral over an infinite-dimensional random function. In this paper we present the first approach to Gaussian Cox processes in which it is possible to perform inference without introducing approximations or finitedimensional proxy distributions. We call our method the Sigmoidal Gaussian Cox Process, which uses a generative model for Poisson data to enable tractable inference via Markov chain Monte Carlo. We compare our methods to competing methods on synthetic data and apply it to several real-world data sets. Copyright 2009.

Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities

The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian process is a useful way to place a prior distribution on this intensity. The combination of a Poisson process and GP is known as a Gaussian Cox process, or doubly-stochastic Poisson process. Likelihood-based inference in these models requires an intractable integral over an infinite-dimensional random function. In this paper we present the first approach to Gaussian Cox processes in which it is possible to perform inference without introducing approximations or finite-dimensional proxy distributions. We call our method the Sigmoidal Gaussian Cox Process, which uses a generative model for Poisson data to enable tractable inference via Markov chain Monte Carlo. We compare our methods to competing methods on synthetic data and apply it to several real-world data sets.

Symmetrical 2-D Hermite-Gaussian square launch for high bit rate transmission in multimode fiber links

A 2-D Hermite-Gaussian square launch is demonstrated to show improved systems capacity over multimode fiber links. It shows a bandwidth improvement over both center and offset launches and exhibits ±5 μm misalignment tolerance. © 2011 Optical Society of America.