Mixture density network training by computation in parameter space

Training Mixture Density Network (MDN) configurations within the NETLAB framework takes time due to the nature of the computation of the error function and the gradient of the error function. By optimising the computation of these functions, so that gradient information is computed in parameter space, training time is decreased by at least a factor of sixty for the example given. Decreased training time increases the spectrum of problems to which MDNs can be practically applied making the MDN framework an attractive method to the applied problem solver.

Inventory parameter management and focused continuous improvement for repetitive batch manufacturers

What this thesis proposes is a methodology to assist repetitive batch manufacturers in the adoption of certain aspects of the Lean Production principles. The methodology concentrates on the reduction of inventory through the setting of appropriate batch sizes, taking account of the effect of sequence dependent set-ups and the identification and elimination of bottlenecks. It uses a simple Pareto and modified EBQ based analysis technique to allocate items to period order day classes based on a combination of each item's annual usage value and set-up cost. The period order day classes the items are allocated to are determined by the constraints limits in the three measured dimensions, capacity, administration and finance. The methodology overcomes the limitations associated with MRP in the area of sequence dependent set-ups, and provides a simple way of setting planning parameters taking this effect into account by concentrating on the reduction of inventory through the systematic identification and elimination of bottlenecks through set-up reduction processes, so allowing batch sizes to reduce. It aims to help traditional repetitive batch manufacturers in a route to continual improvement by: Highlighting those areas where change would bring the greatest benefits. Modelling the effect of proposed changes. Quantifying the benefits that could be gained through implementing the proposed changes. Simplifying the effort required to perform the modelling process. It concentrates on increasing flexibility through managed inventory reduction through rationally decreasing batch sizes, taking account of sequence dependent set-ups and the identification and elimination of bottlenecks. This was achieved through the development of a software modelling tool, and validated through a case study approach.

Q parameter estimation using numerical simulations for linear and nonlinear transmission systems

We compare the Q parameter obtained from scalar, semi-analytical and full vector models for realistic transmission systems. One set of systems is operated in the linear regime, while another is using solitons at high peak power. We report in detail on the different results obtained for the same system using different models. Polarisation mode dispersion is also taken into account and a novel method to average Q parameters over several independent simulation runs is described. © 2006 Elsevier B.V. All rights reserved.

Semi-analytical Q parameter estimate in linear and nonlinear transmission systems

We compare the Q parameter obtained from the semi-analytical model with scalar and vector models for two realistic transmission systems. First a linear system with a compensated dispersion map and second a soliton transmission system.

Numerical Q parameter estimates for scalar and vector models in optical communication system simulations

The Q parameter scales differently with the noise power for the signal-noise and the noise-noise beating terms in scalar and vector models. Some procedures for including noise in the scalar model largely under-estimate the Q parameter. We propose a simple method for including noise within a scalar model which will allow both the noise-noise dominated limit and the signal-noise dominated limit to be treated consistently. © 2005 Elsevier B.V. All rights reserved.

Q parameter scaling in scalar and vector models with dominant signal-noise and noise-noise beating terms

The Q parameter scales differently with the noise power for the signal-noise and the noise-noise beating terms in scalar and vector models. Some procedures for including noise in the scalar model largely under-estimate the Q parameter.

Improved supercontinuum generation by dispersion tuning and dual wavelength pumping

Supercontinuum generation in ultra-long Raman fibre laser cavities is compared for a range of fibre dispersions in the anomalous and normal regimes. For normal dispersion improved performance and efficiency is achieved using dual wavelength pumping.

Electromechanical resonators as measuring transducers

With the increasing use of digital computers for data acquisition and digital process control, frequency domain transducers have become very attractive due to their virtual digital output. Essentially they are electrically maintained oscillators where the sensor is the controlling resonator.They are designed to make the frequency a function of the physical parameter being measured. Because of their high quality factor, mechanical resonators give very good frequency stability and are widely used as sensors. For this work symmetrical mechanical resonators such as the tuning fork were considered, to be the most promising. These are dynamically clamped and can be designed to have extensive regions where no vibrations occur.This enables the resonators to be robustly mounted in a way convenient for various applications. Designs for the measurement of fluid density and tension have been produced. The principle of the design of the resonator for fluid density measurement is a thin gap (trapping a lamina of fluid) between its two members which vibrate in antiphase.An analysis of the inter­ action between this resonator and the fluid lamina has carried out.In gases narrow gaps are needed for a good sensitivity and the use of the material fused quartz, because of its low density and very low temperature coefficient, is ideally suitable. In liquids an adequate sensitivity is achieved even with a wide lamina gap. Practical designs of such transducers have been evolved. The accuracy for liquid measurements is better than 1%. For gases it was found that, in air, a change of atmospheric pressure of 0.3% could be detected. In constructing a tension transducer using such a mechanical sensor as a wire or a beam, major difficulties are encountered in making an efficient clamping arrangement for the sensor. The use of dynamically clamped beams has been found to overcome the problem and this is the basis of the transducer investigated.

Neural population coding is optimized by discrete tuning curves

The sigmoidal tuning curve that maximizes the mutual information for a Poisson neuron, or population of Poisson neurons, is obtained. The optimal tuning curve is found to have a discrete structure that results in a quantization of the input signal. The number of quantization levels undergoes a hierarchy of phase transitions as the length of the coding window is varied. We postulate, using the mammalian auditory system as an example, that the presence of a subpopulation structure within a neural population is consistent with an optimal neural code.