The work described in this thesis concerns the integration of push-pull class B amplifier and antenna modules. Push-pull class B is well-known with its fruitful advantages of using differential feeding technique, resulting in low distortion, reasonably high efficiency and high output power. Meanwhile, the antenna module in this work is adapted from the aperture-coupled antenna structure due to its degree of freedom to control the variables which provide the best possible topology that could be realised in system on chip or system in package. More generally, the variables allow good coverage of the Smith Chart so that a wide range of odd-mode matching requirements could be met, for different devices and bias condition of a given transistor. The approach also offers additional filtering up to 3rd harmonic in that it comprises identical harmonic traps on both sides of the aperture using resonant stubs to form bandstop filters, which reduce the ripples at the output waveforms, giving them a significant advantage of neat and tight integration of a push-pull transmitting amplifier.

Speech signals contain important information about a speaker, such as age, gender, language, accent, and emotional/psychological state. Automatic recognition of these types of characteristics has a wide range of commercial, medical and forensic applications such as interactive voice response systems, service customization, natural human-machine interaction, recognizing the type of pathology of speakers, and directing the forensic investigation process. Many such applications depend on reliable systems using short speech segments without regard to the spoken text (text-independent). All these applications are also applicable using children’s speech. This research aims to develop accurate methods and tools to identify different characteristics of the speakers. Our experiments cover speaker recognition, gender recognition, age-group classification, and accent identification. However, similar approaches and techniques can be applied to identify other characteristics such as emotional/psychological state. The main focus of this research is on detecting these characteristics from children’s speech, which is previously reported as a more challenging subject compared to adult. Furthermore, the impact of different frequency bands on the performances of several recognition systems is studied, and the performance obtained using children’s speech is compared with the corresponding results from experiments using adults’ speech. Speaker characterization is performed by fitting a probability density function to acoustic features extracted from the speech signals. Since the distribution of acoustic features is complex, Gaussian mixture models (GMM) are applied. Due to lack of data, parametric model adaptation methods have been applied to adapt the universal background model (UBM) to the char acteristics of utterances. An effective approach involves adapting the UBM to speech signals using the Maximum-A-Posteriori (MAP) scheme. Then, the Gaussian means of the adapted GMM are concatenated to form a Gaussian mean super-vector for a given utterance. Finally, a classification or regression algorithm is used to identify the speaker characteristics. While effective, Gaussian mean super-vectors are of a high dimensionality resulting in high computational cost and difficulty in obtaining a robust model in the context of limited data. In the field of speaker recognition, recent advances using the i-vector framework have increased the classification accuracy. This framework, which provides a compact representation of an utterance in the form of a low dimensional feature vector, applies a simple factor analysis on GMM means.

This research work focuses on the analysis of multi-layered, anechoic tiles for underwater applications, especially in the field of communications. It is firstly shown how the sound absorbing properties of viscoelastic materials can be modified and enhanced by the proper use of fillers, such as lead oxide and mica. Successively, a new method for identifying the viscoelastic frequency-dependent properties of such materials from experimental data is presented. The method is based on a variational method analogous to the Hamilton Principle. It allows calculating hard-to-find properties such as the complex viscoelastic response functions and the complex Poisson ratio. After the materials properties have been determined, it is shown how they can be incorporated into the combined finite-element-boundary element method to provide accurate numerical solutions to the acoustic scattering problem. A tile made of three layers, a reflecting aluminium layer, an absorbing butyl rubber layer and a matching layer made of a regular grid of polyurethane cones is finally analysed in several scattering and geometrical configurations. The scattering patterns produced by a plane wave incident on the tile are plotted, discussed and compared with experimental data obtained from in-tank scattering measurements of a model tile.

This thesis is the result of study into development, experimental testing and clutter analysis in a Forward Scatter Radar (FSR) designed to detect low reflectivity maritime targets at low grazing angles. The concept of such kind of maritime system is presented; its advantages for surveillance applications are described. Scattering of Electromagnetic (EM) Waves over the sea surface at different radar configurations is outlined with the focus made on forward scattering and appropriate sea clutter models. Phenomenology of the signals in FSR is examined and explained. The development of an experimental FSR hardware operating in X- and K- frequency bands for target detection and clutter analysis and its performance are described in details. It follows with the comprehensive analysis on the measured sea clutter which includes study of influence of a large number of parameters of the radar and sea conditions on the clutter spectral and statistical properties. Finally preliminary analysis of radio frequency (RF) target signatures made with the prototype radar is presented.

The Neuro-Linguistic Programming (NLP) Eye-Accessing Cues (EAC) model suggests that there is a correlation between eye-movements and the internal processing mode that people employ when accessing their subjective experience. Upon careful examination, the experimental methodologies of past research studies were based on assumptions informed by an incomplete or erroneous understanding of the EAC model that could have significantly influenced the experimental results. The reliability of the results can be further impacted by the absence of modern eye-tracking equipment to support the inherently complex task of reliably recording, selecting and rating eye-movements. While a plethora of eye-tracker designs is available to date, none of them has been designed to track non-visual eye-movements (eye-movements that are a result of neuro-physiological events and are not associated with vision), which tend to range outside the normal visual field and thus perform poorly in such cases. Therefore, this thesis introduces a set of novel algorithms for the extraction of relevant eye features (pupil position, iris radius and eye corners) that are combined to calculate the 2D gaze direction and to classify each eye-movement to one of eight classes from the EAC model. The applicability of the eyetracker is demonstrated through a pilot study that serves as a real-world application case study. The performance of the eye-tracker is found to be practical for the intended purpose as it is lightweight, low-cost and can robustly perform the tasks of 2D gaze direction estimation and classification.

The Feynman path integral is used to describe paraxial, scalar wave propagation in weakly inhomogeneous media of the type encountered in passive integrated-optical communication devices. Most of the devices considered in this work are simple models for graded-index waveguide structures, such as tapered and coupled waveguides of a wide variety of geometries. Tapered and coupled graded-index waveguides are the building blocks of waveguide junctions and tapered couplers, and have been mainly studied in the past through numerical simulations. Closed form expressions for the propagator and the coupling efficiency of symmetrically tapered graded-index waveguide sections are presented in this thesis for the first time. The tapered waveguide geometries considered are the general power-law geometry, the linear, parabolic, inverse-square-law, and exponential tapers. Closed form expressions describing the propagation of a centred Gaussian beam in these tapers have also been derived. The approximate propagator of two parallel, coupled graded-index waveguides has also been derived in closed form. An expression for the beat length of this system of coupled waveguides has also been obtained for the cases of strong and intermediate strength coupling. The propagator of two coupled waveguides with a variable spacing was also obtained in terms of an unknown function specified by a second order differential equation with simple boundary conditions. The technique of path integration is finally used to study wave propagation in a number of dielectric media whose refractive index has a random component. A refractive index model of this type is relevant to dielectric waveguides formed using a process of diffusion, and is thus of interest in the study of integrated optical waveguides. We obtained closed form results for the average propagator and the density of propagation modes for Gaussian random media having either zero or infinite refractive-index-inhomogeneity correlation-length along the direction of wave propagation.

As high-temperature superconductor technology approaches commercial applications, for example superconducting magnetic energy storage, superconducting fault current limiters, and superconducting rotary machines for marine propulsion, it is timely to consider the possibility of integrating the associated control equipment into the cryostat with the superconductor. This may bring benefits in terms of the performance of the power electronics or may enable other system benefits such as higher voltage lower current feedthroughs which reduce heat leakage into the cryostat. This Thesis studies the performance of several DC-DC power conversion techniques at temperatures down to 20 K. In particular hard switching, synchronous rectifier, zero-voltageswitching and multi-level circuit prototypes are examined, focusing on the losses in the semiconductor devices. The prototypes operated from 120 V and 500 V DC supplies at power levels up to 500 W using MOSFET devices and ultrafast, Schottky and silicon carbide diodes. The semiconductors were all in commercial TO220 packages. Although MOSFET on-state resistance was found to drop by a factor of approximately six at cryogenic temperatures, the device switching speed and switching losses were relatively insensitive to temperature. The diode on-state voltage increased by 20-30 % at low temperatures whilst reverse recovery and the associated losses decreased by a factor of up to ten. The total semiconductor losses in all prototypes reduced at low temperatures, typically exhibiting a minimum value in the region of 50-100 K. The performance of the hard switching and synchronous rectifier circuits was limited at cryogenic temperatures by switching losses, even though the dead time in the synchronous rectifier was adjusted to compensate for the increase in MOSFET gate threshold voltage at low temperatures. The zero-voltage-switching prototype offered the largest reduction in semiconductor losses at low temperatures, the losses were reduced to 18 % of the room temperature value. Furthermore, since the remaining losses were almost entirely due to MOSFET conduction, further reductions could be easily achieved by paralleling additional devices. The performance of the multi-level circuits was limited by switching losses and the large number of series connected devices; however, a zero-voltage-switching synchronous rectifier variant of the circuit was suggested to overcome some of these limitations.

This study is to maintain and extend the power standards at National Physical Laboratory (NPL) in the United Kingdom. The calibration service of microwave power sensors at high frequencies is endangered because a limited number of traceable waveguide power sensors is available at 50 GHz and above. In this thesis, the technologies of sensing microwave power in waveguides are reviewed, and the bolometric power sensor is investigated further, as its principle is suitable for the traceability requirement at NPL. The conventional design technique of bolometric sensor based on transmission line theory is generalised and two power sensor designs are introduced. The X-band sensor was fabricated, measured at the University of Birmingham and calibrated at NPL. Excellent linearity and high effective efficiency of the design was obtained. The high frequency power sensor designs based on the proposed technique can be scalable to 300 GHz and above, and a W-band sensor is introduced as an example. In order to add more flexibility in selecting frequency and bandwidth, a novel design of microwave power sensor with integrated filter function is described. An analytical power sensor synthesis technique using coupling matrix is presented for the first time. An X-band power sensor with integrated third order Chebyshev filter function was designed and manufactured. Experiential measurements in Birmingham and NPL are in good agreement with simulation and theoretical expectation.

The thesis presents study to explore the role of dynamic features in speaker verification. Based on the theory that dynamic information should contain important speaker information, modelling the dynamics should have the potential to improve the speaker verification performance. Experiments on TD-SV using segmental hidden Markov models (SHMMs) on the YOHO database show performance improvement. However there is no significant improvement for TI-SV from experiments on the Switchboard database, using segmental GMMs. Analysis of the TD-SV results confirms that the speech dynamics modeled by SHMMs contribute more to the SV accuracy. Analysis of the TI-SV results indicates that the lack of speech dynamic information is a feature of GMM systems. It seems that the priority of the maximum likelihood training algorithm is to model stationary regions, and the role of dynamic features in GMM system, is to ensure that the classification focuses on static regions rather than to model dynamics. Study on TI-SV was carried out using conventional GMMs. Without RASTA filtering, the `delta-only' system works best. However, after RASTA filtering, the `static-plus-delta' system performs best. The results suggest that the good performance of the `delta-only' system before RASTA is mainly due to the noise robustness of the delta parameters.

This Thesis presents a model-based interpretation of images that can vary greatly in appearance. Rather than seek characteristic landmarks to model objects we sample points at regular intervals on the boundary to model objects with a smooth boundary. A statistical model of form in the exponent domain of an extended superellipse is created using sampled points and appearance by sampling inside objects. A colour Maximum Likelihood Ratio criterion (MLR) was used to detect cues to the location of potential pedestrians. The adaptability and specificity of this cue detector was evaluated using over 700 images. A True Positive Rate (TPR) of 0.95 and a False Positive Rate (FPR) of 0.20 were obtained. To detect objects with axes at various orientations a variant method using an interpolated colour MLR has been developed. This had a TPR of 0.94 and an FPR of 0.21 when tested over 700 images of pedestrians. Interpretation was evaluated using over 220 video sequences (640 x 480 pixels per frame) and 1000 images of people alone and people associated with other objects. The objective was not so much to evaluate pedestrian detection but the precision and reliability of object delineation. More than 94% of pedestrians were correctly interpreted.