Thesis (M.App.Sc.) - Carleton University, 2005. / Includes bibliographical references (p. 143-146). Also available in electronic format on the Internet.

Thesis (M.App.Sc.) - Carleton University, 2005. / Includes bibliographical references (p. 81-82). Also available in electronic format on the Internet.

Dissertation (PhD)--University of Stellenbosch, 2007. / Bibliography. Also available via the Internet.

Thesis (M.S.)--Oregon State University, 2004. / Typescript (photocopy). Includes bibliographical references (leaves 61-63). Also available on the World Wide Web.

Thesis (M. Eng.)--Carleton University, 1995. / Also available in electronic format on the Internet.

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 59-60).

Thesis (Ph. D.)--Oregon State University, 2007. / Printout. Includes bibliographical references (leaves 107-110). Also available online.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 149-154).

Miniaturisation has been the holy grail of mobile technology. The ability to move around with our gadgets, especially the ones for communication and entertainment, has been what semiconductor scientists have battled over the past decades. Miniaturisation brings about reduced consumption in power and ease of mobility. However, the main impediment to untethered mobility of our gadgets has been the lack of unlimited power supply. The battery had filled this gap for some time, but due to the increased functionalities of these mobile gadgets, increasing the battery capacity would increase the weight of the device considerably that it would eventually become too heavy to carry around. Moreover, the fact that these batteries need to be recharged means we are still not completely free of power cords. The advent of low powered micro-controllers and sensors has created a huge industry for more powerful devices that consume a lot less power. These devices have encouraged hardware designers to reduce the power consumption of the gadgets. This has encouraged the idea of wireless power transmission on another level. With lots of radio frequency energy all around us, from our cordless phones to the numerous mobile cell sites there has not been a better time to delve more into research on WPT. This study looks at the feasibilities of WPT in small device applications where very low power is consumed to carry out some important functionality. The work done here compared two rectifying circuits’ efficiencies and ways to improve on the overall efficiencies. The results obtained show that the full wave rectifier would be the better option when designing a WPT system as more power can be drawn from the rectenna. The load also had a great role as this determined the amount of power drawn from the circuitry.

Advances in VLSI manufacturing and design technology over the decades have created many computing paradigms for disparate computing needs. With concerns for transmission cost, security, latency of centralized computing, edge/local computing are increasingly prevalent in the faster growing sectors like Internet-of-Things (IoT) and other sectors that require energy/connectivity autonomous systems such as biomedical and industrial applications. Energy and power efficient are the main design constraints in local and edge computing. While there exists a wide range of low power design techniques, they are often underutilized in custom circuit designs as the algorithms are developed independent of the hardware. Such compartmentalized design approach fails to take advantage of the many compatible algorithmic and hardware techniques that can improve the efficiency of the entire system. Algorithm hardware co-design is to explore the design space with whole stack awareness. The main goal of the algorithm hardware co-design methodology is the enablement and improvement of small form factor edge and local VLSI systems operating under strict constraints of area and energy efficiency. This thesis presents selected works of application specific digital and mixed-signal integrated circuit designs. The application space ranges from implantable biomedical devices to edge machine learning acceleration.