Ph.D Theses

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10 years of news and resources for members of the IEEE Signal Processing Society

Ph.D Theses

In recent years, the complexity of designing embedded signal processing systems for wireless communications has increased significantly based on the need to support increasing levels of operational flexibility and adaptivity, while also supporting increasing data rates and bandwidths.

This dissertation focuses on statistical signal processing theory and its applications to radar, complex-valued signal processing and model selection.

Cardiac magnetic resonance imaging (CMRI) has been proven to be a valuable source of diagnostic information concerning heart health. One application, myocardial blood flow (MBF) quantification using first-pass contrast-enhanced myocardial perfusion, has aided the detection of coronary artery disease and provides an accurate evaluation of myocardial ischemia, an identifier of coronary artery stenosis.

This work investigates how multipath propagation can be exploited to enhance the accuracy of AoA localization systems. The presented multipath assisted method resembles a fingerprinting approach, matching an AoA measurement vector to a set of reference vectors. 

Location based service (LBS) refers to the applications that depend on a user's location to provide services in various categories including navigation, tracking, advertising, healthcare and billing. With the explosive growing market of mobile phones in recent years, its demand is increasing with new ideas and becoming an irreplaceable part of life.

The standard methods to authenticate a computer or a network user, which typically occur once at the initial log-in, suffer from a variety of vulnerabilities such as masquerading and potential system compromise. An effective solution to this one-time authentication problem is the continuous authentication using behavioral biometrics. 

In the last decade, bioinformatics data has been accumulated at an unprecedented rate, thanks to the advancement in sequencing technologies. Such rapid development poses both challenges and promising research topics. In this dissertation, the authors propose a series of associative pattern recognition algorithms in biological regulation studies.

Speaker age and gender classification is one of the most challenging problems in speech processing. Recently with developing technologies, identifying a speaker age and gender has become a necessity for speaker verification and identification systems such as identifying suspects in criminal cases, improving human-machine interaction, and adapting music for awaiting people queue.

Cardiac magnetic resonance imaging (CMRI) has been proven to be a valuable source of diagnostic information concerning heart health. One application, myocardial blood flow (MBF) quantification using first-pass contrast-enhanced myocardial perfusion, has aided the detection of coronary artery disease and provides an accurate evaluation of myocardial ischemia, an identifier of coronary artery stenosis. 

Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem. Traditional paths to solving this problem include researching more energy-efficient digital topologies as well as digital scaling.

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