Noise modelling and outlier detection in satellite scatterometer data

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Investigation of noise and vibration within an oil flooded sliding vane rotary air compressor

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Experimental demonstration of data-dependent pilot-aided phase noise estimation for CO-OFDM

We demonstrate a novel phase noise estimation scheme for CO-OFDM, in which pilot subcarriers are deliberately correlated to the data subcarriers. This technique reduces the overhead by a factor of 2. © OSA 2014.

Noise and gain optimisation in bi-directionally pumped dispersion compensating amplifier modules

We perform optimisation of bi-directionally pumped dispersion compensating Raman amplifier modules. Optimal forward and backward pump powers for basic configurations using different commercially available fibers are presented for both single- and multi-channel systems. Optical signal-to-noise ratio improvement of up to 8 dB is achieved as a result of optimisation. © 2003 Published by Elsevier B.V.

Statistics of a noise-driven Manakov soliton

We investigate the statistics of a vector Manakov soliton in the presence of additive Gaussian white noise. The adiabatic perturbation theory for a Manakov soliton yields a stochastic Langevin system which we analyse via the corresponding Fokker-Planck equation for the probability density function (PDF) for the soliton parameters. We obtain marginal PDFs for the soliton frequency and amplitude as well as soliton amplitude and polarization angle. We also derive formulae for the variances of all soliton parameters and analyse their dependence on the initial values of polarization angle and phase. © 2006 IOP Publishing Ltd.

Bit-error probability for direct detection of optical RZ signal degraded by ASE noise and timing jitter

We analyze theoretically the interplay between optical return-to-zero signal degradation due to timing jitter and additive amplified-spontaneous-emission noise. The impact of these two factors on the performance of a square-law direct detection receiver is also investigated. We derive an analytical expression for the bit-error probability and quantitatively determine the conditions when the contributions of the effects of timing jitter and additive noise to the bit error rate can be treated separately. The analysis of patterning effects is also presented. © 2007 IEEE.

Statistics of noise-driven coupled nonlinear oscillators:applications to systems with Kerr nonlinearity

We present exact analytical results for the statistics of nonlinear coupled oscillators under the influence of additive white noise. We suggest a perturbative approach for analysing the statistics of such systems under the action of a deterministic perturbation, based on the exact expressions for probability density functions for noise-driven oscillators. Using our perturbation technique we show that our results can be applied to studying the optical signal propagation in noisy fibres at (nearly) zero dispersion as well as to weakly nonlinear lattice models with additive noise. The approach proposed can account for a wide spectrum of physically meaningful perturbations and is applicable to the case of large noise strength. © 2005 Elsevier B.V. All rights reserved.

Span design for reduced noise and nonlinear impairments in a dispersion-managed Raman amplified system

We study a periodic Raman amplified dispersion-managed system with backward-pumping configuration, considering noise and nonlinear impairments. A general optimization method based on nonlinearity management is applied in order to find the configuration that maximizes the system performance. The system is later tested using a full numerical implementation of the nonlinear Schrödinger equation and shown to effectively deliver its longest propagation distance in the same optimal region.

Quasi-pilot aided phase noise estimation for coherent optical OFDM systems

In this letter, a novel phase noise estimation scheme has been proposed for coherent optical orthogonal frequency division multiplexing systems, the quasi-pilot-aided method. In this method, the phases of transmitted pilot subcarriers are deliberately correlated to the phases of data subcarriers. Accounting for this correlation in the receiver allows the required number of pilots needed for a sufficient estimation and compensation of phase noise to be reduced by a factor of 2 in comparison with the traditional pilot-aided phase noise estimation method. We carried out numerical simulation of a 40 Gb/s single polarization transmission system, and the outcome of the investigation indicates that by applying quasi-pilot-aided phase estimation, only four pilot subcarriers are needed for effective phase noise compensation. © 2014 IEEE.

Optimal design for correlated processes with input-dependent noise

Optimal design for parameter estimation in Gaussian process regression models with input-dependent noise is examined. The motivation stems from the area of computer experiments, where computationally demanding simulators are approximated using Gaussian process emulators to act as statistical surrogates. In the case of stochastic simulators, which produce a random output for a given set of model inputs, repeated evaluations are useful, supporting the use of replicate observations in the experimental design. The findings are also applicable to the wider context of experimental design for Gaussian process regression and kriging. Designs are proposed with the aim of minimising the variance of the Gaussian process parameter estimates. A heteroscedastic Gaussian process model is presented which allows for an experimental design technique based on an extension of Fisher information to heteroscedastic models. It is empirically shown that the error of the approximation of the parameter variance by the inverse of the Fisher information is reduced as the number of replicated points is increased. Through a series of simulation experiments on both synthetic data and a systems biology stochastic simulator, optimal designs with replicate observations are shown to outperform space-filling designs both with and without replicate observations. Guidance is provided on best practice for optimal experimental design for stochastic response models. © 2013 Elsevier Inc. All rights reserved.

Study of EEPN mitigation using modified RF pilot and Viterbi-Viterbi based phase noise compensation

We propose - as a modification of the optical (RF) pilot scheme -a balanced phase modulation between two polarizations of the optical signal in order to generate correlated equalization enhanced phase noise (EEPN) contributions in the two polarizations. The method is applicable for n-level PSK system. The EEPN can be compensated, the carrier phase extracted and the nPSK signal regenerated by complex conjugation and multiplication in the receiver. The method is tested by system simulations in a single channel QPSK system at 56 Gb/s system rate. It is found that the conjugation and multiplication scheme in the Rx can mitigate the EEPN to within 1/2 orders of magnitude. Results are compared to using the Viterbi-Viterbi algorithm to mitigate the EEPN. The latter method improves the sensitivity more than two orders of magnitude. Important novel insight into the statistical properties of EEPN is identified and discussed in the paper. © 2013 Optical Society of America.

Critical noise levels for low-density parity check decoding

We determine the critical noise level for decoding low-density parity check error-correcting codes based on the magnetization enumerator (M), rather than on the weight enumerator (W) employed in the information theory literature. The interpretation of our method is appealingly simple, and the relation between the different decoding schemes such as typical pairs decoding, MAP, and finite temperature decoding (MPM) becomes clear. In addition, our analysis provides an explanation for the difference in performance between MN and Gallager codes. Our results are more optimistic than those derived using the methods of information theory and are in excellent agreement with recent results from another statistical physics approach.

Supermode-noise suppression using a nonlinear Fabry–Pérot filter in a harmonically mode-locked fiber ring laser

A simple efficient method for stabilizing a harmonically mode-locked fiber ring laser is proposed. In this method, a linear optical filter and a nonlinear Fabry–Pérot filter in which the refractive index is optical intensity dependent are located in the laser cavity. The linear filter is used to select a fixed lasing wavelength, and the Fabry–Pérot filter introduces a negative all-optical feedback mechanism that is able to suppress pulse-to-pulse amplitude fluctuations in the laser cavity. The scheme was experimentally demonstrated using a fiber Bragg grating as the linear filter and a laser diode biased below threshold as the nonlinear Fabry–Pérot, and stable harmonically mode-locked pulses with a supermode noise suppression ratio >55 dB were obtained.

Noise suppression in a harmonically mode-locked fibre ring laser

A simple and efficient method to stabilise harmonically mode-locked fibre ring laser is proposed. In this method, a linear optical filter and a nonlinear Fabry-Perot filter are introduced into the laser cavity. Stable harmonically mode-locked pulses with supermode noise suppression ratio more than 55dB was demonstrated.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.