Thesis (M. Eng.)--Carleton University, 2001. / Includes bibliographical references (p. 95-97). Also available in electronic format on the Internet.

Thesis (Ph. D.)--Carleton University, 2002. / Includes bibliographical references (p. 166-177). Also available in electronic format on the Internet.

Thesis (M.A.Sc. (Engineering Sc.)) - Simon Fraser University, 2004. / Theses (School of Engineering Science) / Simon Fraser University. Also available on the World Wide Web.

Thesis (M.App.Sc.) - Carleton University, 2007. / Includes bibliographical references (p. 92-94). Also available in electronic format on the Internet.

Thesis (Ph.D.)--McMaster University, 2003. / Advisor: James P. Reilly. Includes bibliographical reference (leaves 142-151). Also available via World Wide Web.

No / The performances of two different angle of arrival estimation algorithms, phase interferometry and covariance based super resolution, and two different mutual coupling compensation methods, conventional and received mutual impedance, have been compared. Two different scenarios have been explored, firstly with a single source transmitter, and then with dual source transmitters. Different powers levels were used to estimate the performance of these algorithms in a multipath/multisource environment over a perfect ground plane. The results show greater accuracy using the covariance based technique, and also support the use of the received mutual impedance method for coupling compensation.

Thesis (M. Eng.)--Carleton University, 2000. / Includes bibliographical references (p. 94-99). Also available in electronic format on the Internet.

No description available.

Yes / Deepfakes constitute fake content -generally in the form of video clips and other media formats such as images or audio- created using deep learning algorithms. With the rapid development of artificial intelligence (AI) technologies, the deepfake content is becoming more sophisticated, with the developed detection techniques proving to be less effective. So far, most of the detection techniques in the literature are based on AI algorithms and can be considered as passive. This paper presents a proof-of-concept deepfake detection system that detects fake news video clips generated using voice impersonation. In the proposed scheme, digital watermarks are embedded in the audio track of a video using a hybrid speech watermarking technique. This is an active approach for deepfake detection. A standalone software application can perform the detection of robust and fragile watermarks. Simulations are performed to evaluate the embedded watermark's robustness against common signal processing and video integrity attacks. As far as we know, this is one of the first few attempts to use digital watermarking for fake content detection. / EIG CONCERT-Japan call to the project entitled “Detection of fake newS on SocIal MedIa pLAtfoRms” (DISSIMILAR) through grants PCI2020-120689-2 (Ministry of Science and Innovation, Spain) and JPMJSC20C3 (JST SICORP, Japan). In addition, the work of the first two authors was partly funded by the Spanish Government through RTI2018-095094-B-C22 “CONSENT”

Large-dimensional communication systems are likely to play an important role in modern wireless communications, where dimensions can be in space, time, frequency and their combinations. Large dimensions can bring several advantages with respect to the performance of communication systems. Harnessing such large-dimension benefits in practice, however, is challenging. In particular, optimum signal detection gets prohibitively complex for large dimensions. Consequently, low-complexity detection techniques that scale well for large dimensions while achieving near-optimal performance are of interest. Belief Propagation (BP) is a technique that solves inference problems using graphical models. BP has been successfully employed in a variety of applications including computational biology, statistical signal/image processing, machine learning and artificial intelligence. BP is well suited in several communication problems as well; e.g., decoding of turbo codes and low-density parity check codes (LDPC), and multiuser detection. We propose a BP based algorithm for detection in large-dimension linear vector channels employing binary phase shift keying (BPSK) modulation, by adopting a Markov random field (MRF)graphical model of the system. The proposed approach is shown to achieve i)detection at low complexities that scale well for large dimensions, and ii)improved bit error performance for increased number of dimensions (a behavior we refer to as the ’large-system behavior’). As one application of the BP based approach, we demonstrate the effectiveness of the proposed BP algorithm for decoding non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA)having large dimensions. We further improve the performance of the proposed algorithm through damped belief propagation, where messages that are passed from one iteration to the next are formed as a weighted combination of messages from the current iteration and the previous iteration. Next, we extend the proposed BP approach to higher order modulation. through a novel scheme of interference cancellation. This proposed scheme exhibits large system behavior in terms of bit error performance, while being scalable to large dimensions in terms of complexity. Finally, as another application of the BP based approach, we illustrate the adoption and performance of the proposed BP algorithm for low-complexity near-optimal equalization in severely delay-spread UWBMIMO-ISI channels that are characterized by large number (tens to hundreds)of multipath components.