We discuss the propagation of wave packets of the form ei(ωt - kz) G(z,t) in an infinite uniform plasma (in both the formal cold plasma, and hot collision-free Vlasov plasma limit), where G(z,t) is a slowly varying function of space z and time t. One can derive the equation of change of G(z,t) (in both the above stated temperature limits) for the stable or unstable case. The terms in the equation are of physical interest and clearly define the limitations of linear theory. In particular we show that by using the model of complete stirring developed by A. C. Das, changes in apparent frequency a0/at (0 = phase of disturbance) can occur due to sharp changes in growth rate with respect to wave number. We then investigate the problem of Whistler mode wave propagation in a collisionless Vlasov plasma in a given non-uniform magnetic field. We choose the electric field to be of a W.K.B. form wad the particle distribution to be isotropic. We can express the perturbation in the particle distribution in terms of an integration along the zero order particle orbits (an integration over time). These orbits can be found correct to a term linear in a smallness parameter ε (when ε equals zero we arrive back at a uniform magnetic field). The charge and current density due to the perturbation are related through Maxwell's equations to the electric and magnetic field of the wave in the usual self consistent Boltzmann-Vlasov description. We show that the contribution to the current arises from recent events in the history of a given particle because of the finite temperature of the plasma. This result leads to an expansion of slowly varying parameters which in turn gives rise to the equation governing the motion of the wave-packet. In the final chapter the monochromatic wave case is also considered and cyclotron resonance is then investigated. It is shown that typically Fresnel integrals arise. Some light is also thrown on the magnetic beach configuration discussed by Stix. For completeness a paper on the modulation of cosmic rays, which was presented by the author at the Ninth International Conference on Cosmic Rays, is also included at the end of this thesis.

For mitigation and monitoring of endangered North Atlantic Right whales, identifying their presence from their vocalisations is the essential principle of Passive Acoustic Monitoring (PAM) system. The most common vocalisations of Right whales are characterized as frequency modulated up sweeps with duration of ~1s and a frequency range from 50 to 200 Hz. These species favour shallow waters during their seasonal migration. Such shallow-water acoustic environments act as a waveguide and cause the mono-component up call emitted by the vocalising whale to become a dispersive multimode signal with different time arrivals and relative energy at the receiver. As well as the natural variation in species vocalisation, another variation in the characteristic features extracted from dispersive calls results from the dispersion effect. In this thesis normal mode modelling was used to better understand the influence of shallow water on the parameters of Right whale up calls. Also, examples from data recorded in Cape Cod Bay shows the dispersion influence. Visual scanning indicates that 93% of the data are dispersive and the first mode in 85% of these calls is less excited than the second mode due to the dependence of mode excitation on the depth of the calling whale. The discrimination between the Northern Right whale up calls and background noise has been investigated using the Support Vector Machine classifier. To perform this task, a region-based active contour segmentation method is proposed. This approach is based on the evolution of the contour within the spectrogram image searching for the uniformity of the target object. In this work both synthesized data based on typical Right whale vocalisations and real data recorded in Cape Cod Bay are used to evaluate the proposed method. To illustrate the variation in the data caused by the channel effect we compare the descriptive statistics of the call duration using both the single mode and the multi-mode approaches. The single mode analysis was performed by extracting the frequency contour of the first mode.

This thesis deals with the implementation of the dual reciprocity boundary element method for problems governed by the Helmholtz equation. The main emphasis is the simulation of acoustic cavities, such as passenger compartments of aeroplanes and of cars. The boundary element method is a numerical analysis scheme which only needs a discretisation of the boundary of the domain of interest. The dual reciprocity boundary element method is a variation of this technique. The advantage of applying this special scheme for the Helmholtz equation is that in the final equation, unlike with the 'classical' boundary element method, the matrices are independent of the wave number. The Helmholtz problems in this research involve different geometries, properties and dimensions. A total of seven codes are employed, ranging from one- to three-dimensional problem solvers. The one-dimensional code is capable of solving related eigenfrequency and wave generation problems. Three of the two-dimensional codes are applied to eigenfrequency analysis: one is based on the constant element, one uses linear elements and one employs quadratic elements. A final two-dimensional code is used for wave propagation problems and uses the constant element. The three-dimensional codes are applied to eigenfrequency analysis only; one uses constant triangular elements, and another employs linear triangular elements. The kernel integrations in the two- and three-dimensional codes are all based on analytical solutions, given in this thesis. A new method of quadratic element kernel integration is described in detail. The three-dimensional triangular boundary element kernel integrations are based on improved analytical formulations.

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Owing to the random nature of audio signals, most of the enhancement methodologies reviewed in this work are based explicitly on a Bayesian model-based approach. Of these, the Kalman filter is the most commonly adopted enhancement strategy for a linear and Gaussian restoration problem. To copy with the general non-linear and non-Gaussian case, different filters such as the extended Kalman filter and the Gaussian sum filter have been proposed in the past few decades. As computing power increases, more computationally expensive simulation based approaches such as Monte Carlo methods have been suggested. The main focus of this work is on sequential estimation of the underlying clean signal and system parameters given some noisy observations under the Monte Carlo framework. This class of method is known as sequential Monte Carlo methods, also commonly referred to as the particle filter. In this work, different improvement strategies have been developed and described to improve on the generic particle filtering/smoothing algorithm. A block-based particle smoother is proposed to reduce the memory capacity required for the processing of lengthy datasets, such as audio signals. A Rao-Blackwellised particle smoother is developed to improve on the simulation results by reducing the dimension of the sampling space and thus the estimation variance. To cope with the non-linear restoration problem, a non-linear Rao-Blackwellised particle smoother is developed, which marginalises the parameter state, instead of the signal state as suggested earlier. Finally, we propose an efficient implementation of the suggested slow time-varying model under the sequential Monte Carlo framework for on-line joint signal and parameter estimation.

The prediction of vibration and noise has long been a problem in many fields. It has become increasingly important because of safety and environmental legislation, and its study has benefited from increasingly powerful computer technology. This thesis concentrates on acoustically generated vibrations in ship hulls, particularly those of cruise liners. These vibrations must be predicted and understood so that passenger comfort can be ensured and operational restrictions met. In order to analyse vibration one needs to bring together an acoustic model appropriate to the form of the propeller, hull and operating environment, a numerical technique that can reliably solve the resulting equations and an effective and accurate way of representing the complex hull shapes involved. Because of the complexity of the problem, progress on understanding vibration in real situations needs computational analysis. A numerical method must be established which has the potential to be used for optimal design of the shapes involved in such structures. The acoustic model is based upon the Helmholtz wave equation with a distribution of sources representing the propellers and hull. The numerical technique used is the boundary element method. The value of the boundary element method compared with other common techniques lies in the fact that it reduces the dimension of the problem and hence simplifies the boundary conditions required as input. The partial differential equation (PDE) method is used to represent the hull. The advantage of this method is that it can represent and manipulate real ship geometries in an effective efficient and accurate way. This thesis proposes an approach to predicting the propeller-induced vibration. The work is novel in its application of boundary elements together with the partial differential equation (PDE) surface method to vibration problems. The work has already been used to predict vibration on <I>Aurora</I>, the latest P&O cruise ship, prior to its launch.

Particle Filter-based Acoustic Source Localisation algorithms track (online and in real-time) the position of a sound source – a person speaking in a room – based on the current data from a microphone array as well as all previous data up to that point. The first section of this thesis reviews previous research in this field and discusses the suitability of using particle filters to solve this problem. Experiments are then detailed which examine the typical performance and behaviour of various instantaneous localisation functions. In subsequent sections, algorithms are detailed which advance the state-of-the-art. First an orientation estimation algorithm is introduced which uses speaker directivity to infer head pose. Second an algorithm is introduced for multi-target acoustic source tracking and is based upon the Track Before Detect (TBD) methodology. Using this methodology avoids the need to identify a set of source measurements and allows for a large saving in computational power. Finally this algorithm is extended to allow for an unknown and time-varying number of speakers. By leveraging the frequency content of speech it is shown that regions of the surveillance space can be monitored for activity while requiring only a minor increase in overall computation. A variable dimension particle filter is then outlined which proposes newly active targets, maintains target tracks and removes targets when they become inactive.

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