Influence of Current Pulse Shape on Directly Modulated Systems Performance in Metro Area Optical Networks

Due to the fact that a metro network market is very cost sensitive, direct modulated schemes appear attractive. In this paper a CWDM (Coarse Wavelength Division Multiplexing) system is studied in detail by means of an Optical Communication System Design Software; a detailed study of the modulated current shape (exponential, sine and gaussian) for 2.5 Gb/s CWDM Metropolitan Area Networks is performed to evaluate its tolerance to linear impairments such as signal-to-noise-ratio degradation and dispersion. Point-to-point links are investigated and optimum design parameters are obtained. Through extensive sets of simulation results, it is shown that some of these shape pulses are more tolerant to dispersion when compared with conventional gaussian shape pulses. In order to achieve a low Bit Error Rate (BER), different types of optical transmitters are considered including strongly adiabatic and transient chirp dominated Directly Modulated Lasers (DMLs). We have used fibers with different dispersion characteristics, showing that the system performance depends, strongly, on the chosen DML?fiber couple.

EMI filter design of a three-phase buck-type rectifier for aircraft applications

An EMI filter for a three-phase buck-type medium power pulse-width modulation rectifier is designed. This filter considers differential mode noise and complies with MIL-STD- 461E for the frequency range of 10kHz to 10MHz. In industrial applications, the frequency range of the standard starts at 150kHz and the designer typically uses a switching frequency of 28kHz because the fifth harmonic is out of the range. This approach is not valid for aircraft applications. In order to design the switching frequency in aircraft applications, the power losses in the semiconductors and the weight of the reactive components should be considered. The proposed design is based on a harmonic analysis of the rectifier input current and an analytical study of the input filter. The classical industrial design does not consider the inductive effect in the filter design because the grid frequency is 50/60Hz. However, in the aircraft applications, the grid frequency is 400Hz and the inductance cannot be neglected. The proposed design considers the inductance and the capacitance effect of the filter in order to obtain unitary power factor at full power. In the optimization process, several filters are designed for different switching frequencies of the converter. In addition, designs from single to five stages are considered. The power losses of the converter plus the EMI filter are estimated at these switching frequencies. Considering overall losses and minimal filter volume, the optimal switching frequency is selected

New Considerations in the Input Filter Design of a Three-Phase Buck-Type PWM Rectifier for Aircraft Applications

An EMI filter for a three-phase buck-type medium power pulse-width modulation rectifier is designed. This filter considers differential mode noise and complies with MIL-STD-461E for the frequency range of 10kHz to 10MHz. In industrial applications, the frequency range of the standard starts at 150kHz and the designer typically uses a switching frequency of 28kHz because the fifth harmonic is out of the range. This approach is not valid for aircraft applications. In order to design the switching frequency in aircraft applications, the power losses in the semiconductors and the weight of the reactive components should be considered. The proposed design is based on a harmonic analysis of the rectifier input current and an analytical study of the input filter. The classical industrial design does not consider the inductive effect in the filter design because the grid frequency is 50/60Hz. However, in the aircraft applications, the grid frequency is 400Hz and the inductance cannot be neglected. The proposed design considers the inductance and the capacitance effect of the filter in order to obtain unitary power factor at full power. In the optimization process, several filters are designed for different switching frequencies of the converter. In addition, designs from single to five stages are considered. The power losses of the converter plus the EMI filter are estimated at these switching frequencies. Considering overall losses and minimal filter volume, the optimal switching frequency is selected.

Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm

This work evaluates a spline-based smoothing method applied to the output of a glucose predictor. Methods:Our on-line prediction algorithm is based on a neural network model (NNM). We trained/validated the NNM with a prediction horizon of 30 minutes using 39/54 profiles of patients monitored with the Guardian® Real-Time continuous glucose monitoring system The NNM output is smoothed by fitting a causal cubic spline. The assessment parameters are the error (RMSE), mean delay (MD) and the high-frequency noise (HFCrms). The HFCrms is the root-mean-square values of the high-frequency components isolated with a zero-delay non-causal filter. HFCrms is 2.90±1.37 (mg/dl) for the original profiles.

Glucose-Insulin regulator for type 1 diabetes using high order neural networks

In this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas? beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed- Loop (CL). Tests in Semi-Closed-Loop (SCL) are made feedforward in order to give information to the control algorithm. We conclude the controller is able to drive the glucose to target in overnight periods and the feedforward is necessary to control the postprandial period.

Long-term but not short-term plasticity at mossy fiber synapses is impaired in neural cell adhesion molecule-deficient mice

Cell adhesion molecules (CAMs) are known to be involved in a variety of developmental processes that play key roles in the establishment of synaptic connectivity during embryonic development, but recent evidence implicates the same molecules in synaptic plasticity of the adult. In the present study, we have used neural CAM (NCAM)-deficient mice, which have learning and behavioral deficits, to evaluate NCAM function in the hippocampal mossy fiber system. Morphological studies demonstrated that fasciculation and laminar growth of mossy fibers were strongly affected, leading to innervation of CA3 pyramidal cells at ectopic sites, whereas individual mossy fiber boutons appeared normal. Electrophysiological recordings performed in hippocampal slice preparations revealed that both basal synaptic transmission and two forms of short-term plasticity, i.e., paired-pulse facilitation and frequency facilitation, were normal in mice lacking all forms of NCAM. However, long-term potentiation of glutamatergic excitatory synapses after brief trains of repetitive stimulation was abolished. Taken together, these results strongly suggest that in the hippocampal mossy fiber system, NCAM is essential both for correct axonal growth and synaptogenesis and for long-term changes in synaptic strength.

An approach to probe some neural systems interaction by functional MRI at neural time scale down to milliseconds

In this paper, we demonstrate an approach by which some evoked neuronal events can be probed by functional MRI (fMRI) signal with temporal resolution at the time scale of tens of milliseconds. The approach is based on the close relationship between neuronal electrical events and fMRI signal that is experimentally demonstrated in concurrent fMRI and electroencephalographic (EEG) studies conducted in a rat model with forepaw electrical stimulation. We observed a refractory period of neuronal origin in a two-stimuli paradigm: the first stimulation pulse suppressed the evoked activity in both EEG and fMRI signal responding to the subsequent stimulus for a period of several hundred milliseconds. When there was an apparent site–site interaction detected in the evoked EEG signal induced by two stimuli that were primarily targeted to activate two different sites in the brain, fMRI also displayed signal amplitude modulation because of the interactive event. With visual stimulation using two short pulses in the human brain, a similar refractory phenomenon was observed in activated fMRI signals in the primary visual cortex. In addition, for interstimulus intervals shorter than the known latency time of the evoked potential induced by the first stimulus (≈100 ms) in the primary visual cortex of the human brain, the suppression was not present. Thus, by controlling the temporal relation of input tasks, it is possible to study temporal evolution of certain neural events at the time scale of their evoked electrical activity by noninvasive fMRI methodology.

Bayesian regression filter and the issue of priors

We propose a Bayesian framework for regression problems, which covers areas which are usually dealt with by function approximation. An online learning algorithm is derived which solves regression problems with a Kalman filter. Its solution always improves with increasing model complexity, without the risk of over-fitting. In the infinite dimension limit it approaches the true Bayesian posterior. The issues of prior selection and over-fitting are also discussed, showing that some of the commonly held beliefs are misleading. The practical implementation is summarised. Simulations using 13 popular publicly available data sets are used to demonstrate the method and highlight important issues concerning the choice of priors.

Classification of oximetry signals using Bayesian neural networks to assist in the detection of obstructive sleep apnoea syndrome

In the present study, multilayer perceptron (MLP) neural networks were applied to help in the diagnosis of obstructive sleep apnoea syndrome (OSAS). Oxygen saturation (SaO2) recordings from nocturnal pulse oximetry were used for this purpose. We performed time and spectral analysis of these signals to extract 14 features related to OSAS. The performance of two different MLP classifiers was compared: maximum likelihood (ML) and Bayesian (BY) MLP networks. A total of 187 subjects suspected of suffering from OSAS took part in the study. Their SaO2 signals were divided into a training set with 74 recordings and a test set with 113 recordings. BY-MLP networks achieved the best performance on the test set with 85.58% accuracy (87.76% sensitivity and 82.39% specificity). These results were substantially better than those provided by ML-MLP networks, which were affected by overfitting and achieved an accuracy of 76.81% (86.42% sensitivity and 62.83% specificity). Our results suggest that the Bayesian framework is preferred to implement our MLP classifiers. The proposed BY-MLP networks could be used for early OSAS detection. They could contribute to overcome the difficulties of nocturnal polysomnography (PSG) and thus reduce the demand for these studies.

Spatial contrast sensitivity and external noise: applications to optical and neural modulation transfer functions

The thesis will show how to equalise the effect of quantal noise across spatial frequencies by keeping the retinal flux (If-2) constant. In addition, quantal noise is used to study the effect of grating area and spatial frequency on contrast sensitivity resulting in the extension of the new contrast detection model describing the human contrast detection system as a simple image processor. According to the model the human contrast detection system comprises low-pass filtering due to ocular optics, addition of light dependent noise at the event of quantal absorption, high-pass filtering due to the neural visual pathways, addition of internal neural noise, after which detection takes place by a local matched filter, whose sampling efficiency decreases as grating area is increased. Furthermore, this work will demonstrate how to extract both the optical and neural modulation transfer functions of the human eye. The neural transfer function is found to be proportional to spatial frequency up to the local cut-off frequency at eccentricities of 0 - 37 deg across the visual field. The optical transfer function of the human eye is proposed to be more affected by the Stiles-Crawford -effect than generally assumed in the literature. Similarly, this work questions the prevailing ideas about the factors limiting peripheral vision by showing that peripheral optical acts as a low-pass filter in normal viewing conditions, and therefore the effect of peripheral optics is worse than generally assumed.

All-fiber-integrated soliton-similariton laser with in-line fiber filter

We demonstrate an all-fiber-integrated Er-doped fiber laser operating in the soliton-similariton mode-locking regime. In the similariton part of the cavity, a self-similarly evolving parabolic pulse with highly linear chirp propagates in the presence of normal dispersion. Following an in-line fiber-based birefringent filter, the pulse evolves into a soliton in the part of the cavity with anomalous dispersion. The similariton and the soliton pulses are dechirped to 75.5 and 167.2 fs, respectively, outside of the cavity. Mode-locked operation is very robust, owing to the influence of the two similariton and soliton attractors that predominate each half of the laser cavity. The experimental results are supported with numerical simulations, which provide good agreement.

Simultaneous ultrafast optical pulse train bursts generation and shaping based on Fourier series developments using superimposed fiber Bragg gratings

We propose an all-fiber method for the generation of ultrafast shaped pulse train bursts from a single pulse based on Fourier Series Developments (FDSs). The implementation of the FSD based filter only requires the use of a very simple non apodized Superimposed Fiber Bragg Grating (S-FBG) for the generation of the Shaped Output Pulse Train Burst (SOPTB). In this approach, the shape, the period and the temporal length of the generated SOPTB have no dependency on the input pulse rate.

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.

Tailored waveform generation in mode-locked fiber lasers by in-cavity pulse shaper

We numerically show the possibility of pulse shaping in a mode-locked fiber laser by inclusion of an amplitude-phase spectral filter into the laser cavity. Various advanced temporal waveforms are generated, including parabolic, flat-top and triangular pulses. © 2014 OSA.

In-cavity transformations for new nonlinear regimes of pulse generation in mode-locked fibre lasers

We review recent progress in the research on nonlinear mechanisms of pulse generation in passively mode-locked fibre lasers. These include parabolic self-similar pulse mode-locking, a mode-locking regime featuring pulses with a triangular distribution of the intensity, and spectral compression arising from nonlinear pulse propagation. We also report on the possibility of achieving various regimes of advanced temporal waveform generation in a mode-locked fibre laser by inclusion of a spectral filter into the laser cavity.