Traditional signal detection algorithms are often robust and are typically sufficient for high SNR data. However, the assumptions behind these methods begin to fall apart when signal period becomes either very short, or small in amplitude compared to any corruptive noise. To address this a kernel transform based cross-correlation algorithm is proposed for the application of weak signal detection. The algorithm leverages kernel methods to inflate SNR of the data and enhance the noise rejection capabilities of the traditional cross-correlation. The goal of the algorithm is to achieve detection for signals past the limits of those of the matched filter and the cross-correlation in the presence of white and colored noise. To evaluate the effectiveness of the correlation algorithm, Monte Carlo simulations are performed to determine the performance in the context of different types of noise. The performance of the algorithm will be compared against the cross-correlation and the matched filter. / Master of Science / As society advances, the tools we rely on become increasingly more intricate. Pivotal to the development of these systems is the algorithms used to process the data they collect. Particularly crucial to the field of signal processing, weak signal detection is focused on the processing of barely comprehensible data in the context of powerful noise. In recent years, advancements in weak signal detection have focused on pushing the theoretical limits of signal discernibility, especially when heavily obscured by noise. Leveraging the power of machine learning, certain AI algorithms have showcased promise in the detection of weak signals. It has yet to be seen if a foundational principle of AI called a kernel transform can be applied to classic signal detection theory to increase detection performance. This thesis will propose a kernel based detection algorithm for weak signal detection and the performance of the algorithm will be compared against previously established theory. New breakthroughs in detection algorithms facilitate improvements in active and passive sonar, medical devices and even the finance sector.

Call number: LD2668 .T4 1979 F63 / Master of Science

This dissertation begins with a study of some of the linear and nonlinear optical properties of composite materials consisting of CdSₓSe₁₋ₓ microcrystallites embedded in a host glass matrix. These studies investigate changes in absorption, refractive index and nonlinear response time under a variety of experimental conditions. The data demonstrates that this class of materials exhibit: a strong saturation of absorption due to band filling; a large n₂ which also saturates; response times which range from <100ps to many nanoseconds; and a permanent darkening and change of n₂ induced by extended exposure to high energy pulses. These measurements were used to identify the optimum sample of the semiconductor doped glasses to demonstrate an efficient degenerate four-wave mixing process within a planar waveguide. High quality single mode waveguides were fabricated from the semiconductor doped glass by K⁺-ion exchange. Four wave mixing was performed in the waveguide that produced a peak reflectivity of ≅.003, which is 8 orders of magnitude larger than that achieved previously in a similar experiment where CS₂ was used as the nonlinear medium.

No description available.

International Telemetering Conference Proceedings / October 22-25, 1984 / Riviera Hotel, Las Vegas, Nevada / For maritime applications of distress communications via geostationary satellites a special method of signal processing was developed, called superposition technique. The data frame containing the alert message is transmitted from a distress equipment repeatedly. After being relayed by the satellite the signal is detected and improved by superimposing the frames. Around 14 dB is the actual processing gain. Thus a distress buoy is able to transfer a message from all over the world with high reliability by only transmitting a power of 50 mW omnidirectionally over a slant range of about 40 000 km. The described system, called the Distress Radio Call System (DRCS) was tested in a Coordinated Trials Program (CTP) of 6 nations. Both in a simulation phase and in a field test under exactly the same environmental conditions the DRCS with its superposition technique was able to detect signals with lowest signal-to-noise-density ratio without error. In laboratory tests using GAUSS channel conditions, a system threshold of 13 dB-Hz could be demonstrated. In a real environment (North Cape) 15 dB-Hz was the lower limit for error-free reception. CCIR approved a recommendation in June, 1984 for a system operating through geostationary satellites at 1.6 GHz being a DRCS-type with very little modifications.

Paralinguistic events are useful indicators of the affective state of a speaker. These cues, in children's speech, are used to form social bonds with their caregivers. They have also been found to be useful in the very early detection of developmental disorders such as autism spectrum disorder (ASD) in children's speech. Prior work on children's speech has focused on the use of a limited number of subjects which don't have sufficient diversity in the type of vocalizations that are produced. Also, the features that are necessary to understand the production of paralinguistic events is not fully understood. To account for the lack of an off-the-shelf solution to detect instances of laughter and crying in children's speech, the focus of the thesis is to investigate and develop signal processing algorithms to extract acoustic features and use machine learning algorithms on various corpora. Results obtained using baseline spectral and prosodic features indicate the ability of the combination of spectral, prosodic, and dysphonation-related features that are needed to detect laughter and whining in toddlers' speech with different age groups and recording environments. The use of long-term features were found to be useful to capture the periodic properties of laughter in adults' and children's speech and detected instances of laughter to a high degree of accuracy. Finally, the thesis focuses on the use of multi-modal information using acoustic features and computer vision-based smile-related features to detect instances of laughter and to reduce the instances of false positives in adults' and children's speech. The fusion of the features resulted in an improvement of the accuracy and recall rates than when using either of the two modalities on their own.

The rapid growth of mobile users and emergence of high data rate multimedia and interactive services have resulted in a shortage of the radio spectrum. Novel solutions are therefore required for future generations of wireless networks to enhance capacity and coverage. This thesis aims at addressing this issue through the design and analysis of signal processing algorithms. In particular various resource allocation and spatial diversity techniques have been proposed within the context of wireless peer-to-peer relays and coordinated base station (BS) processing. In order to enhance coverage while providing improvement in capacity, peer-to-peer relays that share the same frequency band have been considered and various techniques for designing relay coefficients and allocating powers optimally are proposed. Both one-way and two-way amplify and forward (AF) relays have been investigated. In order to maintain fairness, a signal-to-interference plus noise ratio (SINR) balancing criterion has been adopted. In order to improve the spectrum utilization further, the relays within the context of cognitive radio network are also considered. In this case, a cognitive peer-to-peer relay network is required to achieve SINR balancing while maintaining the interference leakage to primary receiver below a certain threshold. As the spatial diversity techniques in the form of multiple-input-multipleoutput (MIMO) systems have the potential to enhance capacity significantly, the above work has been extended to peer-to-peer MIMO relay networks. Transceiver and relay beamforming design based on minimum mean-square error (MSE) criterion has been proposed. Establishing uplink downlink MSE duality, an alternating algorithm has been developed. A scenario where multiple users are served by both the BS and a MIMO relay is considered and a joint beamforming technique for the BS and the MIMO relay is proposed. With the motivation of optimising the transmission power at both the BS and the relay, an interference precoding design is presented that takes into account the knowledge of the interference caused by the relay to the users served by the BS. Recognizing joint beamformer design for multiple BSs has the ability to reduce interference in the network significantly, cooperative multi-cell beamforming design is proposed. The aim is to design multi-cell beamformers to maximize the minimum SINR of users subject to individual BS power constraints. In contrast to all works available in the literature that aimed at balancing SINR of all users in all cells to the same level, the SINRs of users in each cell is balanced and maximized at different values. This new technique takes advantage of the fact that BSs may have different available transmission powers and/or channel conditions for their users.

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy