Correcting errors in optical data transmission using neural networks

Optical data communication systems are prone to a variety of processes that modify the transmitted signal, and contribute errors in the determination of 1s from 0s. This is a difficult, and commercially important, problem to solve. Errors must be detected and corrected at high speed, and the classifier must be very accurate; ideally it should also be tunable to the characteristics of individual communication links. We show that simple single layer neural networks may be used to address these problems, and examine how different input representations affect the accuracy of bit error correction. Our results lead us to conclude that a system based on these principles can perform at least as well as an existing non-trainable error correction system, whilst being tunable to suit the individual characteristics of different communication links.

2R and 3R optical regeneration in 40 Gbit/s WDM terrestrial networks

We analyse a 2R regenerator using nonlinear-optical-loop-mirror and a 3R regenerator employing nonlinearly-enhanced amplitude modulator in 40Gbit/s WDM networks based on standard fibre (SMF). Characterization of one- (600km of SMF) and two-step regeneration is presented.

Fiber optical parametric amplifier in high-speed WDM networks

We report high-capacity (> 1 Tb/s) amplification by a fiber optical parametric amplifier in different roles displaying compatibility and versatility in future WDM networks with phase-shift keying modulation format.

Effects of crosstalk in WDM optical label switching networks due to wavelength switching of a tunable laser

Crosstalk caused by switching events in fast tunable lasers in an optical label switching (OLS) system is investigated for the first time. A wavelength-division-multiplexed OLS system based on subcarrier multiplexed labels is presented which employs a 40-Gb/s duobinary payload and a 155-Mb/s label on a 40-GHz subcarrier. Degradation in system performance as the transmitters switch between different channels is then characterized in terms of the frequency drift of the tunable laser.

Data Protection and Packet Mode in the Distributed Information Measurement and Control System for Research in Physics

The present paper is devoted to creation of cryptographic data security and realization of the packet mode in the distributed information measurement and control system that implements methods of optical spectroscopy for plasma physics research and atomic collisions. This system gives a remote access to information and instrument resources within the Intranet/Internet networks. The system provides remote access to information and hardware resources for the natural sciences within the Intranet/Internet networks. The access to physical equipment is realized through the standard interface servers (PXI, CАМАC, and GPIB), the server providing access to Ethernet devices, and the communication server, which integrates the equipment servers into a uniform information system. The system is used to make research task in optical spectroscopy, as well as to support the process of education at the Department of Physics and Engineering of Petrozavodsk State University.

Two cascaded SOAs used as intensity modulators for adaptively modulated optical OFDM signals in optical access networks

Detailed theoretical and numerical investigations of the transmission performance of adaptively modulated optical orthogonal frequency division multiplexed (AMOOFDM) signals are undertaken, for the first time, in optical amplification and chromatic dispersion (CD) compensation free single mode fiber (SMF) intensity-modulated and directdetection (IMDD) systems using two cascaded semiconductor optical amplifiers in a counterpropagating configuration as an intensity modulator (TC-SOA-CC-IM). A theoretical model describing the characteristics of this configuration is developed. Extensive performance comparisons are also made between the TC-SOA-CC and the single SOA intensity modulators. It is shown that, the TC-SOA-CC reaches its strongly saturated region using a lower input optical power much faster than the single SOA resulting in significantly reduced effective carrier lifetime and thus wide TC-SOA-CC bandwidths. It is shown that at low input optical power, we can increase the signal line rate almost 115% which will be more than twice the transmission performance offered by single SOA. In addition, the TCSOA-CC-IM is capable of supporting signal line rates higher than corresponding to the SOA-IM by using 10dB lower input optical powers. For long transmission distance, the TC-SOA-CC-IM has much stronger CD compensation capability compared to the SOA-IM. In addition the use of TC-SOA-CC-IM is more effective regarding the capability to benefit from the CD compensation for shorter distances starting at 60km SMF, whilst for the SOA-IM starting at 90km. © 2014 Optical Society of America.

Differential polarization decoding for robust coherent optical packet switched networks

This paper proposes the use of the 2-D differential decoding to improve the robustness of dual-polarization optical packet receivers and is demonstrated in a wavelength switching scenario for the first time.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Biofouling protection by electro-chlorination on optical windows for oceanographic sensors and imaging devices

Oceans environmental monitoring and seafloor exploitation need in situ sensors and optical devices (cameras, lights) in various locations and on various carriers in order to initiate and to calibrate environmental models or to operate underwater industrial process supervision. For more than 10 years Ifremer deploys in situ monitoring systems for various seawater parameters and in situ observation systems based on lights and HD Cameras. To be economically operational, these systems must be equipped with a biofouling protection dedicated to the sensors and optical devices used in situ. Indeed, biofouling, in less than 15 days [1] will modify the transducing interfaces of the sensors and causes unacceptable bias on the measurements provided by the in situ monitoring system. In the same way biofouling will decrease the optical properties of windows and thus altering the lighting and the quality fot he images recorded by the camera.

Generative Neural Networks for image iper-resolution and improvement of Optical Character Recognition's performances

The usage of Optical Character Recognition’s (OCR, systems is a widely spread technology into the world of Computer Vision and Machine Learning. It is a topic that interest many field, for example the automotive, where becomes a specialized task known as License Plate Recognition, useful for many application from the automation of toll road to intelligent payments. However, OCR systems need to be very accurate and generalizable in order to be able to extract the text of license plates under high variable conditions, from the type of camera used for acquisition to light changes. Such variables compromise the quality of digitalized real scenes causing the presence of noise and degradation of various type, which can be minimized with the application of modern approaches for image iper resolution and noise reduction. Oneclass of them is known as Generative Neural Networks, which are very strong ally for the solution of this popular problem.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Performance analysis of an optical network employing waveband and traffic grooming

This paper analyses an optical network architecture composed by an arrangement of nodes equipped with multi-granular optical cross-connects (MG-OXCs) in addition to the usual optical cross-connects (OXCs). Then, selected network nodes can perform both waveband as well as traffic grooming operations and our goal is to assess the improvement on network performance brought by these additional capabilities. Specifically, the influence of the MG-OXC multi-granularity on the blocking probability is evaluated for 16 classes of service over a network based on the NSFNet topology. A mechanism of fairness in bandwidth capacity is also added to the connection admission control to manage the blocking probabilities of all kind of bandwidth requirements. Comprehensive computational simulation are carried out to compare eight distinct node architectures, showing that an adequate combination of waveband and single-wavelength ports of the MG-OXCs and OXCs allow a more efficient operation of a WDM optical network carrying multi-rate traffic.

Quantum-state protection in cavities

We show how an initially prepared quantum state of a radiation mode in a cavity can be preserved for a long time using a feedback scheme based on the injection of appropriately prepared atoms. We present a feedback scheme both for optical cavities, which can be continuously monitored by a photodetector, and for microwave cavities, which can be monitored only indirectly via the detection of atoms that have interacted with the cavity field. We also discuss the possibility of applying these methods for decoherence control in quantum information processing.

Protection of wind energy systems against the indirect effects of lightning

This paper is concerned with the protection of wind energy systems against the indirect effects of lightning. As wind energy is gaining increasing importance throughout the world, lightning damages involving wind energy systems have come to be regarded with more attention. Nevertheless, there are still very few studies in Portugal regarding lightning protection of wind energy systems using models of the Electro-Magnetic Transients Program (EMTP). Hence, a new case study is presented in this paper, based on a wind turbine with an interconnecting transformer, considering that lightning strikes the soil near the tower at a distance such that galvanic coupling occurs through the grounding electrode. Computer simulations obtained by using EMTP-RV are presented and conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.