Nonlinearity management in fibre links with distributed amplification

An approach to nonlinearity management in optical transmission lines with periodic dispersion compensation and distributed Raman amplification was presented. The optimization of a three-step dispersion map with forward and backward pumped distributed amplification was examined. The optimization was performed using the analytical solution obtained under the assumption of undepleted pumps and without inclusion of double Rayleigh Scattering (DRS), and by means of a full numerical approach accounting for all important effects. It was found that both procedures led to the same final solution.

Dispersion and nonlinearity-management in mode-locked fibre lasers

In this work we extend theory of dispersion-managed (DM) solitons to dissipative systems with the main focus on applications in mode-locked lasers. In general, pulses in mode-locked fibre lasers experience both nonlinear and dispersion management per cavity round trip. In stretched-pulse lasers, this concept was utilized to obtain high energy pulses. Here we model the pulse propagation in a mode-locked fibre laser with a distributed nonlinear and DM Ginzburg-Landau type equation. We extend existing results on DM solitons and investigate the impact on soliton properties of dissipative perturbations that occur due to the effects of gain amplification, saturable absorption, and loss. In conclusion, in contrast to standard DM solitons in Hamiltonian systems, dissipative DM solitons do exist at high map strengths, thus opening a way for the generation of stable, short pulses with high energy.

Dispersion and nonlinearity-management in mode-locked fibre lasers

In this work we extend theory of dispersion-managed (DM) solitons to dissipative systems with the main focus on applications in mode-locked lasers. In general, pulses in mode-locked fibre lasers experience both nonlinear and dispersion management per cavity round trip. In stretched-pulse lasers, this concept was utilized to obtain high energy pulses. Here we model the pulse propagation in a mode-locked fibre laser with a distributed nonlinear and DM Ginzburg-Landau type equation. We extend existing results on DM solitons and investigate the impact on soliton properties of dissipative perturbations that occur due to the effects of gain amplification, saturable absorption, and loss. In conclusion, in contrast to standard DM solitons in Hamiltonian systems, dissipative DM solitons do exist at high map strengths, thus opening a way for the generation of stable, short pulses with high energy.

Modeling of spectral and statistical properties of a random distributed feedback fiber laser

For the first time we report full numerical NLSE-based modeling of generation properties of random distributed feedback fiber laser based on Rayleigh scattering. The model which takes into account the random backscattering via its average strength only describes well power and spectral properties of random DFB fiber lasers. The influence of dispersion and nonlinearity on spectral and statistical properties is investigated. The evidence of non-gaussian intensity statistics is found. © 2013 Optical Society of America.

Multilevel system optimisation via nonlinearity management

Nonlinearity management is explored as a multilevel tool to obtain maximum transmission reach in a WDM system. A technique for the fast calculation of the optimal dispersion pre-compensation in systems with distributed amplification is proposed. © 2005 Optical Society of America.

NLSE-based model of a random distributed feedback fiber laser

In this work we propose a NLSE-based model of power and spectral properties of the random distributed feedback (DFB) fiber laser. The model is based on coupled set of non-linear Schrödinger equations for pump and Stokes waves with the distributed feedback due to Rayleigh scattering. The model considers random backscattering via its average strength, i.e. we assume that the feedback is incoherent. In addition, this allows us to speed up simulations sufficiently (up to several orders of magnitude). We found that the model of the incoherent feedback predicts the smooth and narrow (comparing with the gain spectral profile) generation spectrum in the random DFB fiber laser. The model allows one to optimize the random laser generation spectrum width varying the dispersion and nonlinearity values: we found, that the high dispersion and low nonlinearity results in narrower spectrum that could be interpreted as four-wave mixing between different spectral components in the quasi-mode-less spectrum of the random laser under study could play an important role in the spectrum formation. Note that the physical mechanism of the random DFB fiber laser formation and broadening is not identified yet. We investigate temporal and statistical properties of the random DFB fiber laser dynamics. Interestingly, we found that the intensity statistics is not Gaussian. The intensity auto-correlation function also reveals that correlations do exist. The possibility to optimize the system parameters to enhance the observed intrinsic spectral correlations to further potentially achieved pulsed (mode-locked) operation of the mode-less random distributed feedback fiber laser is discussed.

Solution to reduce nonlinearity in LTE RoF system for an efficient das topology:a brief review

In this paper, a review on radio-over-fiber (RoF) technology is conducted to support the exploding growth of mobile broadband. An RoF system will provide a platform for distributed antenna system (DAS) as a fronthaul of long term evolution (LTE) technology. A higher splitting ratio from a macrocell is required to support large DAS topology, hence higher optical launch power (OLP) is the right approach. However, high OLP generates undesired nonlinearities, namely the stimulated Brillouin scattering (SBS). Three different aspects of solving the SBS process are covered in this paper, where the solutions ultimately provided an additional 4 dB link budget.

The design and evaluation of distributed virtual environment to support learning in global operations management

The primary goal of this research is to design and develop an education technology to support learning in global operations management. The research implements a series of studies to determine the right balance among user requirements, learning methods and applied technologies, on a view of student-centred learning. This research is multidisciplinary by nature, involving topics from various disciplines such as global operations management, curriculum and contemporary learning theory, and computer aided learning. Innovative learning models that emphasise on technological implementation are employed and discussed throughout this research.

Combining spatially distributed predictions from neural networks

In this report we discuss the problem of combining spatially-distributed predictions from neural networks. An example of this problem is the prediction of a wind vector-field from remote-sensing data by combining bottom-up predictions (wind vector predictions on a pixel-by-pixel basis) with prior knowledge about wind-field configurations. This task can be achieved using the scaled-likelihood method, which has been used by Morgan and Bourlard (1995) and Smyth (1994), in the context of Hidden Markov modelling

Distributed algorithms for global optimization on sparse networks of arbitrary bandwidths

The optimization of resource allocation in sparse networks with real variables is studied using methods of statistical physics. Efficient distributed algorithms are devised on the basis of insight gained from the analysis and are examined using numerical simulations, showing excellent performance and full agreement with the theoretical results.

Development of a co-operative distributed process mining system for quality assurance

In this paper, a co-operative distributed process mining system (CDPMS) is developed to streamline the workflow along the supply chain in order to offer shorter delivery times, more flexibility and higher customer satisfaction with learning ability. The proposed system is equipped with the ‘distributed process mining’ feature which is used to discover the hidden relationships among each working decision in distributed manner. This method incorporates the concept of data mining and knowledge refinement into decision making process for ensuring ‘doing the right things’ within the workflow. An example of implementation is given, based on the case of slider manufacturer.

Nonlinearity in all-night sleep EEG recorded with foramen ovale electrodes in a patient with temporal lobe epilepsy

Objective: It is investigated to which extent measures of nonlinearity derived from surrogate data analysis are capable to quantify the changes of epileptic activity related to varying vigilance levels. Methods: Surface and intracranial EEG from foramen ovale (FO-)electrodes was recorded from a patient with temporal lobe epilepsy under presurgical evaluation over one night. Different measures of nonlinearity were estimated for non-overlapping 30-s segments for selected channels from surface and intracranial EEG. Additionally spectral measures were calculated. Sleep stages were scored according to Rechtschaffen/Kales and epileptic transients were counted and classified by visual inspection. Results: In the intracranial recordings stronger nonlinearity was found ipsilateral to the epileptogenic focus, more pronounced in NREM sleep, weaker in REM sleep. The dynamics within the NREM episodes varied with the different nonlinearity measures. Some nonlinearity measures showed variations with the sleep cycle also in the intracranial recordings contralateral to the epileptic focus and in the surface EEG. It is shown that the nonlinearity is correlated with short-term fluctuations of the delta power. The higher frequency of occurrence of clinical relevant epileptic spikes in the first NREM episode was not clearly reflected in the nonlinearity measures. Conclusions: It was confirmed that epileptic activity renders the EEG nonlinear. However, it was shown that the sleep dynamics itself also effects the nonlinearity measures. Therefore, at the present stage it is not possible to establish a unique connection between the studied nonlinearity measures and specific types of epileptic activity in sleep EEG recordings.

Perceiving edge blur: Gaussian-derivative filtering and a rectifying nonlinearity

We studied the visual mechanisms that encode edge blur in images. Our previous work suggested that the visual system spatially differentiates the luminance profile twice to create the `signature' of the edge, and then evaluates the spatial scale of this signature profile by applying Gaussian derivative templates of different sizes. The scale of the best-fitting template indicates the blur of the edge. In blur-matching experiments, a staircase procedure was used to adjust the blur of a comparison edge (40% contrast, 0.3 s duration) until it appeared to match the blur of test edges at different contrasts (5% - 40%) and blurs (6 - 32 min of arc). Results showed that lower-contrast edges looked progressively sharper. We also added a linear luminance gradient to blurred test edges. When the added gradient was of opposite polarity to the edge gradient, it made the edge look progressively sharper. Both effects can be explained quantitatively by the action of a half-wave rectifying nonlinearity that sits between the first and second (linear) differentiating stages. This rectifier was introduced to account for a range of other effects on perceived blur (Barbieri-Hesse and Georgeson, 2002 Perception 31 Supplement, 54), but it readily predicts the influence of the negative ramp. The effect of contrast arises because the rectifier has a threshold: it not only suppresses negative values but also small positive values. At low contrasts, more of the gradient profile falls below threshold and its effective spatial scale shrinks in size, leading to perceived sharpening.

A model for motion sharpening: contrast gain control precedes compressive nonlinearity

Blurred edges appear sharper in motion than when they are stationary. We have previously shown how such distortions in perceived edge blur may be explained by a model which assumes that luminance contrast is encoded by a local contrast transducer whose response becomes progressively more compressive as speed increases. To test this model further, we measured the sharpening of drifting, periodic patterns over a large range of contrasts, blur widths, and speeds Human Vision. The results indicate that, while sharpening increased with speed, it was practically invariant with contrast. This contrast invariance cannot be explained by a fixed compressive nonlinearity since that predicts almost no sharpening at low contrasts.We show by computational modelling of spatiotemporal responses that, if a dynamic contrast gain control precedes the static nonlinear transducer, then motion sharpening, its speed dependence, and its invariance with contrast can be predicted with reasonable accuracy.