Electro-thermal theory of intermodulation distortion in lossy microwave components

An analytic formulation of dynamic electro-thermally induced nonlinearity is developed for a general resistive element, yielding a self-heating circuit model based on a fractional derivative. The model explains the 10 dB/decade slope of the intermodulation products observed in two-tone testing. Two-tone testing at 400 MHz of attenuators, microwave chip terminations, and coaxial terminations is reported with tone spacing ranging from 1 to 100 Hz.

A timing-specific memory distortion effect in young children

It has been suggested that there are systematic distortions in children's memory for temporal durations, such that children's memory is not just less accurate than that of adults but qualitatively different. Experiment I replicated the memory distortion effect by demonstrating developmental change in the tendency to confuse a reference duration with one that is shorter rather than longer than it. When the long-term memory demands of the task were reduced by providing reminders of the reference duration on every trial, there were no such qualitative changes in error patterns (Experiment 2). Further evidence for developmental changes in memory distortion was found in the temporal generalization task of Experiment 3, in which stimuli were spaced logarithmically rather than linearly. In Experiment 4, a similar distortion pattern was absent in a task in which children made judgments about the pitch rather than the duration of stimuli, suggesting the effect may be specific to time estimation. (C) 2003 Elsevier Inc. All rights reserved.

DISTORTION MAPS FROM PREFERENTIAL HYPERACUITY PERIMETRY ARE HELPFUL IN MONITORING FUNCTIONAL RESPONSE TO LUCENTIS THERAPY

Purpose: To use preferential hyperacuity perimetry to obtain a quantitative measure of central visual field distortion that would aid in the monitoring of functional responsiveness to ranibizumab treatment.

Computational Investigation of Inlet Distortion at High Angles of Attack

Lip separation is one of the primary sources of inlet distortion, which can result in a loss in fan stability. High angles of incidence are one of several critical causes of lip separation. There have been many studies into inlet performance at high incidence, including the resulting distortion levels when lip separation occurs. However, the vast majority of these investigations have been carried out experimentally, with little in the way of computational results for inlet performance at high incidence. The flow topology within an inlet when lip separation has occurred is also not well understood. This work aims to demonstrate a suitable model for the prediction of inlet flows at high incidence using ANSYS CFX, looking at both the performance of the inlet and the separated flow topology within the inlet. The attenuating effect of the fan is also investigated, with particular emphasis on the flow redistribution ahead of the fan. The results show that the model used is suitable for predicting inlet performance in adverse operating conditions, showing good agreement with experimental results. In addition, the attenuation of the distortion by the fan is also captured by the numerical model.

The Influence of Friction Stir Welding Process Idealization on Residual Stress and Distortion Predictions for Future Airframe Assembly Simulations

The ability to accurately predict residual stresses and resultant distortions is a key product from process assembly simulations. Assembly processes necessarily consider large structural components potentially making simulations computationally expensive. The objective herein is to develop greater understanding of the influence of friction stir welding process idealization on the prediction of residual stress and distortion and thus determine the minimum required modeling fidelity for future airframe assembly simulations. The combined computational and experimental results highlight the importance of accurately representing the welding forging force and process speed. In addition, the results emphasize that increased CPU simulation times are associated with representing the tool torque, while there is potentially only local increase in prediction fidelity.

Day-Ahead Optimal Charging/Discharging Scheduling for Electric Vehicles in Micro-Grids

A micro-grid is an autonomous system which can be operated and connected to an external system or isolated with the help of energy storage systems (ESSs). While the daily output of distributed generators (DGs) strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the imbalance between the daily load and generation curves. In this paper, a statistical model is presented to describe daily EV charging/discharging behaviour. An optimisation problem is proposed to obtain economic operation for the micro-grid based on this model. In day-ahead scheduling, with estimated information of power generation and load demand, optimal charging/discharging of EVs during 24 hours is obtained. A series of numerical optimization solutions in different scenarios is achieved by serial quadratic programming. The results show that optimal charging/discharging of EVs, a daily load curve can better track the generation curve and the network loss and required ESS capacity are both decreased. The paper also demonstrates cost benefits for EVs and operators.

Characterisation of nonlinear distortion and intermodulation in passive devices and antennas

The paper presents a conceptual discussion of the characterisation and phenomenology of passive intermodulation (PIM) by the localised and distributed nonlinearities in passive devices and antennas. The PIM distinctive nature and its impact on signal distortions are examined in comparison with similar effects in power amplifiers. The main features of PIM generation are discussed and illustrated by the example of PIM due to electro-thermal nonlinearity. The issues of measurement, discrimination and modelling of PIM generated by nonlinearities in passive RF components and antennas are addressed.

Distributed MPC for Frequency Regulation in Multi-Terminal HVDC Grids

High Voltage Direct Current (HVDC) lines allow large quantities of power to be
transferred between two points in an electrical power system. A Multi-Terminal HVDC (MTDC) grid consists of a meshed network of HVDC lines, and this allows energy reserves to be shared between a number of AC areas in an efficient manner. Secondary Frequency Control (SFC) algorithms return the frequencies in areas connected by AC or DC lines to their original setpoints after Primary Frequency Controllers have been called following a contingency. Where multiple
TSOs are responsible for different parts of a MTDC grid it may not be possible to implement SFC from a centralised location. Thus, in this paper a simple gain based distributed Model Predictive Control strategy is proposed for Secondary Frequency Control of MTDC grids which allows TSOs to cooperatively perform SFC without the need for centralised coordination.

Polarization Distortion as a Means for Securing Wireless Communication

This paper presents a simple polarization encoding strategy that operates using only single element dual port transmit and receive antennas in such a way that selective spatial scrambling of QPSK data can be effected. The key transmitter and receiver relationships needed for this operation to occur are derived. The system is validated using a cross dipole antenna arrangement. Unlike all previously reported physical layer wireless solutions the approach developed in this paper transfers the security property to the receive side resulting in very simple transmit and receive side architectures thus avoiding the need for near field modulated array technology. In addition the scheme permits, for the first time, multiple spatially separated secured receive sites to operate in parallel.

Droop setting design for multi-terminal HVDC grids considering voltage deviation impacts

In multi-terminal high voltage direct current (HVDC) grids, the widely deployed droop control strategies will cause a non-uniform voltage deviation on the power flow, which is determined by the network topology and droop settings. This voltage deviation results in an inconsistent power flow pattern when the dispatch references are changed, which could be detrimental to the operation and seamless integration of HVDC grids. In this paper, a novel droop setting design method is proposed to address this problem for a more precise power dispatch. The effects of voltage deviations on the power sharing accuracy and transmission loss are analysed. This paper shows that there is a trade-off between minimizing the voltage deviation, ensuring a proper power delivery and reducing the total transmission loss in the droop setting design. The efficacy of the proposed method is confirmed by simulation studies.

An iterative longest matching segment approach to speech enhancement with additive noise and channel distortion

This paper presents a new approach to speech enhancement from single-channel measurements involving both noise and channel distortion (i.e., convolutional noise), and demonstrates its applications for robust speech recognition and for improving noisy speech quality. The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise for speech estimation. Third, we present an iterative algorithm which updates the noise and channel estimates of the corpus data model. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement.

Speech Enhancement from Additive Noise and Channel Distortion - a Corpus-Based Approach

This paper presents a new approach to single-channel speech enhancement involving both noise and channel distortion (i.e., convolutional noise). The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise. Third, we present an iterative algorithm for improved speech estimates. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement. Index Terms: corpus-based speech model, longest matching segment, speech enhancement, speech recognition