In speaker verification, the mismatches between the training speech and the testing speech can greatly affect the robustness of classification algorithms, and the mismatches are mainly caused by the changes in the noise types and the signal to noise ratios. This thesis aims at finding the most robust classification methods under multi-noise and multiple signal to noise ratio conditions. Comparison of several well-known state of the art classification algorithms and features in speaker verification are made through examining the performance of small-set speaker verification system (e.g. voice lock for a family). The effect of the testing speech length is also examined. The i-vector/Probabilistic Linear Discriminant Analysis method with compensation strategies is shown to provide a stable performance for both previously seen and previously unseen noise scenarios, and a C++ implementation with online processing and multi-threading is developed for this approach.

Initial investigations of the Outlier Processing Method (OPM), first introduced by Birch [1][2][3] in 1988, have demonstrated a promising ability to extract a special class of signals, called highly variable events (HVEs), from coloured noise processes. The term HVE is introduced in this thesis to identify a finite-duration signal whose shape and latency vary dramatically from trial to trial and typically has a very low signal-to-noise ratio (SNR). This thesis presents a modified version of the original OPM algorithm, which can generate an estimate of the HVE with significantly less estimation noise than the original OPM algorithm. Simulation experiments are used to identify the strengths and limitations of this modified OPM algorithm for linear and stationary processes and to compare the modified algorithm's performance to the performance of the original algorithm and to the performance of a minimum mean-square-error (MMSE) filter. The results of these experiments verify that the modified algorithm can extract an HVE with less estimation noise than the original algorithm. The results also show, that the MMSE filter is unsuitable for extracting HVEs and that its performance is generally inferior to the modified algorithm's performance. The experiments indicate that the modified algorithm can extract HVEs from a linear and stationary process for SNR levels above -2.5dB and can work effectively above -7.5dB for HVEs with certain characteristics. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

The thesis describes experimental techniques used and results obtained in the investigation of the pure tone components of sound radiation from a commercial 19 inch axial flow fan. The causes and extent of the discrete tone sources were investigated by several methods: cross-correlation of fan surface pressure fluctuations with far field sound, spectral analysis of surface pressure, and examination of surface pressure waveforms. A unique feature involved the design of an apparatus for detecting and transmitting fan-borne pressure fluctuations off the rotating blades. "Causality Correlations" with the on-axis far field sound rendered dipole source strength distribution functions over a span wise line at 15 per cent chord from the leading edge of the fan blade and around a circumferential ring on the motor support strut at a fan radius of 89 per cent. Results indicate that the on-axis discrete tones are a result of source mechanisms causing force fluctuations on the blades and struts which in turn lead to sound radiation which is dipole in nature and is most intense on the axis of the fan. These mechanisms include ingestion of a concentrated vortex, modulation of the clearance between the blade tips and the fan shroud, flow separation around the inlet bell mouth, and fluctuations in the inflow velocity due to the proximity of the fan to the wedged wall of the Anechoic chamber. Crude integral approximations of source strength distributions over the surfaces of the blades and the struts indicated that sound radiation at the blade passage frequency from these two contributors to the overall sound would be about equal, although more sound radiation is expected to originate at the rotor. / Applied Science, Faculty of / Mechanical Engineering, Department of / Graduate

The thesis deals with speckle suppression in images acquired by optical coherence tomograph. It is divided into four parts. The first part describes basic information about the medical imaging method. It also deals with principle of measurement. The second section discusses the formation of image speckle and selected methods to reduce them. Next part is practical and consists of data acquisition, determination of the evaluation methodology and the implementation of speckle reduction methods. The last part is focused on testing and reviews of algorithms and discussion about their results.

Thesis is focused on the impact of the inside noise of the car on conditional driver safety, which is presented by reaction times on simulated stimulus. In introduction, there is a theoretical definition of the security of the vehicles, inside noise, and its methods of measurement. Practical part consists of description and realization of the measurements of the impact on the inside noise in the car on reaction time of drivers. Conclusion includes evaluations of the measurements and findings, which results from them.

Active noise reduction was first proposed as a solution for environmental noise over fifty years ago. The use of active noise reduction (ANR) systems, however, was not demonstrated until much later. Recent advances in technology have made the use of active noise reduction systems in personal hearing protection devices (HPDs) practical. Through the use of advanced electronics technology, ANR equipped devices offer the potential to provide increased low frequency attenuation for hearing conservation applications. In order to use ANR equipped devices in an Occupational Safety and Health Administration (OSHA) sanctioned hearing conservation program, a testing standard for ANR equipped HPDs needs to be developed. Existing HPD testing standards offer the most promise for developing an acceptable standard for testing ANR-equipped HPDs. The microphone in real ear (MIRE) testing method is one method that offers a practical method for determining the performance of ANR devices for use in hearing conservation programs. A modified version of this method was successfully used in this study to determine the performance profile of an open-back ANR equipped headset. The results of this and other studies that have used a modified MIRE testing method can be used to support the acceptance of this method as the basis of an approved standard for testing ANR-equipped hearing protection devices. / Master of Science

The effects of noise correlations on neuronal stimulus discrimination have been the subject of sustained debate. Both experimental and computational work suggest beneficial and detrimental contributions of noise correlations. The aim of this study is to develop an analytically tractable model of stimulus discrimination that reveals the conditions leading to improved or impaired performance from model parameters and levels of noise correlation. We begin with a mean firing rate integrator model as an approximation of underlying spiking activity in neuronal circuits. We consider two independent units receiving constant input and time fluctuating noise whose correlation across units can be tuned independently of firing rate. We implement a perceptron-like readout with Fisher Linear Discriminant Analysis (LDA). We exploit its closed form solution to find explicit expressions for discrimination error as a function of network parameters (leak, shared inputs, and noise gain) as well as the strength of noise correlation. First, we derive equations for discrimination error as a function of noise correlation. We find that four qualitatively different sets of results exist, based on the ratios of the difference of means and variance of the distributions of neural activity. From network parameters, we find the conditions for which an increase in noise correlation can lead to monotonic decrease or monotonic increase of error, as well as conditions for which error evolves non-monotonically as a function of correlations. These results provide a potential explanation for previously reported contradictory effects of noise correlation. Second, we expand on the dependency of the quantitative behaviour of the error curve on the tuning of specific subsets of network parameters. Particularly, when the noise gain of a pair of units is increased, the error rate as a function of noise correlation increases multiplicatively. However, when the noise gain of a single unit is increased, under certain conditions, the effect of noise can be beneficial to stimulus discrimination. In sum, we present a framework of analysis that explains a series of non-trivial properties of neuronal discrimination via a simple linear classifier. We show explicitly how different configurations of parameters can lead to drastically different conclusions on the impact of noise correlations. These effects shed light on abundant experimental and computational results reporting conflicting effects of noise correlations. The derived analyses rely on few assumptions and may therefore be applicable to a broad class of neural models whose activity can be approximated by a multivariate distribution.

Research focusing on static scenes with static objects is omitting the time factor from real life examples we are trying to study. Can we say that a lifeguard looking for a drowning man is using the same brain processes that were observed in the laboratory for static scenes? We can conclude that a static scene is a big simplification of the task itself. The aim of this thesis is to prepare a tool which would allow researching dynamic scenes and thus broadening the possibilities of visual detection tasks at hand. Along the tool we also present a couple of simplified examples with which we would like to demonstrate the utilization of the tool. All concluding with a final experiment in which we will try to detect masked patterns in a noisy environment. 1

Boat noise has been shown to distract and cause harm to many marine organisms. Most of the study effort has been focused on fish & marine mammals, even though invertebrates represent 99% of all living organisms, both terrestrial and aquatic. The small amount of studies conducted on invertebrates have demonstrated a clear negative correlation between anthropogenic noise pollution and invertebrate well-being. The small giant clam Tridacna maxima and the spider conch Lambis lambis are two invertebrate species which play key roles in coral reef ecosystems, and are little studied for the effects of noise disturbance. If their behaviour is significantly affected by boat noise, this could cause a knock on effect on the rest of the reef ecosystem. T. maxima functions as prey to many fish species, contributing up to 9% of the reef’s calcium carbonate budget, as well as playing a role in nutrient cycling. L. lambis is essential prey for molluscivore snails and certain elasmobranchs, and through its herbivorous feeding, helps to keep filamentous algae levels low. Moreover, coral reefs are reliant on the biological sound primarily created by invertebrates, such as snapping shrimp, to attract larvae from the pelagic environment for settlement. During experiments conducted in February 2020 in the Red Sea, Daily Diary Monitoring (DDMT) smart tags were used to measure the reactions of T. maxima and L. lambis respectively during underwater playback of boat noise compared with ambient reef sound. It was found that both T. maxima and L. lambis exhibited behavioral changes during the boat noise treatment. The implications of this study is that individuals of L. lambis and T. maxima may spend energy averting the invisible "threat" of boat noise, rather than feeding and/or photosynthesizing, in the case of T. maxima. If this hinders the acquisition of food/production, the whole reef ecosystem may be compromised in a knock-on effect from these producers and primary consumers. As boat noise is prevalent on inshore Red Sea reefs, shown by a 24-hour acoustic analysis of a patch reef sound pressure levels (SPL), invertebrates might be affected on a large scale in the Red Sea.

As the technology is advances the reduced size of hardware gives rise to an additive 1/f baseband noise. This additive 1/f noise is a system noise generated due to miniaturization of hardware and affects the lower frequencies. Though 1/f noise does not show much effect in wide band channels because of its nature to affect only certain frequencies, 1/f noise becomes a prominent in OFDM communication systems where narrow band channels are used. in this thesis, I study the effects of 1/f noise on the OFDM systems and implement algorithms for estimation and suppression of the noise using Kalman filter. Suppression of the noise is achieved by subtracting the estimated noise from the received noise. I show that the performance of the system is considerably improved by applying the 1/f noise suppression.