Uncoded space-time labelling diversity : data rate & reliability enhancements and application to real-world satellite broadcasting.

Doctoral Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF

Scalable video compression

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1992.Includes bibliographical references (leaves 85-88).by Joseph Bruce Stampleman.M.S

Program Mikrokontroler Untuk Menampilkan Tingkat Ketegangan Otot

Program Mikrokontroler Untuk Menampilkan Tingkat Ketegangan Oto

Integrated Sensing and Communications: Recent Advances and Ten Open Challenges

It is anticipated that integrated sensing and communications (ISAC) would be one of the key enablers of next-generation wireless networks (such as beyond 5G (B5G) and 6G) for supporting a variety of emerging applications. In this paper, we provide a comprehensive review of the recent advances in ISAC systems, with a particular focus on their foundations, system design, networking aspects and ISAC applications. Furthermore, we discuss the corresponding open questions of the above that emerged in each issue. Hence, we commence with the information theory of sensing and communications (S$\&$C), followed by the information-theoretic limits of ISAC systems by shedding light on the fundamental performance metrics. Next, we discuss their clock synchronization and phase offset problems, the associated Pareto-optimal signaling strategies, as well as the associated super-resolution ISAC system design. Moreover, we envision that ISAC ushers in a paradigm shift for the future cellular networks relying on network sensing, transforming the classic cellular architecture, cross-layer resource management methods, and transmission protocols. In ISAC applications, we further highlight the security and privacy issues of wireless sensing. Finally, we close by studying the recent advances in a representative ISAC use case, namely the multi-object multi-task (MOMT) recognition problem using wireless signals.Comment: 26 pages, 22 figures, resubmitted to IEEE Journal. Appreciation for the outstanding contributions of coauthors in the paper

IIR modeling of interpositional transfer functions with a genetic algorithm aided by an adaptive filter for the purpose of altering free-field sound localization

The psychoacoustic process of sound localization is a system of complex analysis. Scientists have found evidence that both binaural and monaural cues are responsible for determining the angles of elevation and azimuth which represent a sound source. Engineers have successfully used these cues to build mathematical localization systems. Research has indicated that spectral cues play an important role in 3-d localization. Therefore, it seems conceivable to design a filtering system which can alter the localization of a sound source, either for correctional purposes or listener preference. Such filters, known as Interpositional Transfer Functions, can be formed from division in the z-domain of Head-related Transfer Functions. HRTF’s represent the free-field response of the human body to sound processed by the ears. In filtering applications, the use of IIR filters is often favored over that of FIR filters due to their preservation of resolution while minimizing the number of required coefficients. Several methods exist for creating IIR filters from their representative FIR counterparts. For complicated filters, genetic algorithms (GAs) have proven effective. The research summarized in this thesis combines the past efforts of researchers in the fields of sound localization, genetic algorithms, and adaptive filtering. It represents the initial stage in the development of a practical system for future hardware implementation which uses a genetic algorithm as a driving engine. Under ideal conditions, an IIR filter design system has been demonstrated to successfully model several IPTF pairs which alter sound localization when applied to non-minimum phase HRTF’s obtained from free-field measurement

Multiuser Detection in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing Systems by Blind Signal Separation Techniques

This dissertation introduces three novel multiuser detection approaches in Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems by blind signal separation (BSS) techniques. The conventional methodologies for multiuser detection have to retransmit channel state information (CSI) constantly from the transmitter in MIMO ODFM systems at the cost of economic efficiency, because they require more channel resources to improve the communication quality. Compared with the traditional methodologies, the proposed BSS methods are relatively efficient approaches without the unnecessary retransmission of channel state information. The current methodologies apply the space-time coding or the spatial multiplexing to implement an MIMO OFDM system, which requires relatively complex antenna design and allocation in the transmitter. The proposed Spatial Division Multiple Access (SDMA) method enables different mobile users to share the same bandwidth simultaneously in different geographical locations, and this scheme requires only one antenna for each mobile user. Therefore, it greatly simplifies the antenna design and allocation. The goal of this dissertation is to design and implement three blind multiuser detection schemes without knowing the channel state information or the channel transfer function in the SDMA-based uplink MIMO OFDM system. The proposed scenarios include: (a) the BSS-only scheme, (b) the BSS-Minimum Mean Square Error (MMSE) scheme, and (c) the BSS-Minimum Bit Error Ratio (MBER) scheme. The major contributions of the dissertation include: (a) the three proposed schemes save the commercially expensive cost of channel resources; (b) the proposed SDMA-based uplink MIMO OFDM system simplifies the requirements of antennas for mobile users; (c) the three proposed schemes obtain high parallel computing efficiency through paralleled subcarriers; (d) the proposed BSS-MBER scheme gains the best BER performance; (e) the proposed BSS-MMSE method yields the best computational efficiency; and (f) the proposed BSS-only scenario balances the BER performance and computational complexity

Human-Centered Content-Based Image Retrieval

Retrieval of images that lack a (suitable) annotations cannot be achieved through (traditional) Information Retrieval (IR) techniques. Access through such collections can be achieved through the application of computer vision techniques on the IR problem, which is baptized Content-Based Image Retrieval (CBIR). In contrast with most purely technological approaches, the thesis Human-Centered Content-Based Image Retrieval approaches the problem from a human/user centered perspective. Psychophysical experiments were conducted in which people were asked to categorize colors. The data gathered from these experiments was fed to a Fast Exact Euclidean Distance (FEED) transform (Schouten & Van den Broek, 2004), which enabled the segmentation of color space based on human perception (Van den Broek et al., 2008). This unique color space segementation was exploited for texture analysis and image segmentation, and subsequently for full-featured CBIR. In addition, a unique CBIR-benchmark was developed (Van den Broek et al., 2004, 2005). This benchmark was used to explore what and how several parameters (e.g., color and distance measures) of the CBIR process influence retrieval results. In contrast with other research, users judgements were assigned as metric. The online IR and CBIR system Multimedia for Art Retrieval (M4ART) (URL: http://www.m4art.org) has been (partly) founded on the techniques discussed in this thesis. References: - Broek, E.L. van den, Kisters, P.M.F., and Vuurpijl, L.G. (2004). The utilization of human color categorization for content-based image retrieval. Proceedings of SPIE (Human Vision and Electronic Imaging), 5292, 351-362. [see also Chapter 7] - Broek, E.L. van den, Kisters, P.M.F., and Vuurpijl, L.G. (2005). Content-Based Image Retrieval Benchmarking: Utilizing Color Categories and Color Distributions. Journal of Imaging Science and Technology, 49(3), 293-301. [see also Chapter 8] - Broek, E.L. van den, Schouten, Th.E., and Kisters, P.M.F. (2008). Modeling Human Color Categorization. Pattern Recognition Letters, 29(8), 1136-1144. [see also Chapter 5] - Schouten, Th.E. and Broek, E.L. van den (2004). Fast Exact Euclidean Distance (FEED) transformation. In J. Kittler, M. Petrou, and M. Nixon (Eds.), Proceedings of the 17th IEEE International Conference on Pattern Recognition (ICPR 2004), Vol 3, p. 594-597. August 23-26, Cambridge - United Kingdom. [see also Appendix C

Rake, Peel, Sketch:The Signal Processing Pipeline Revisited

The prototypical signal processing pipeline can be divided into four blocks. Representation of the signal in a basis suitable for processing. Enhancement of the meaningful part of the signal and noise reduction. Estimation of important statistical properties of the signal. Adaptive processing to track and adapt to changes in the signal statistics. This thesis revisits each of these blocks and proposes new algorithms, borrowing ideas from information theory, theoretical computer science, or communications. First, we revisit the Walsh-Hadamard transform (WHT) for the case of a signal sparse in the transformed domain, namely that has only K †N non-zero coefficients. We show that an efficient algorithm exists that can compute these coefficients in O(K log2(K) log2(N/K)) and using only O(K log2(N/K)) samples. This algorithm relies on a fast hashing procedure that computes small linear combinations of transformed domain coefficients. A bipartite graph is formed with linear combinations on one side, and non-zero coefficients on the other. A peeling decoder is then used to recover the non-zero coefficients one by one. A detailed analysis of the algorithm based on error correcting codes over the binary erasure channel is given. The second chapter is about beamforming. Inspired by the rake receiver from wireless communications, we recognize that echoes in a room are an important source of extra signal diversity. We extend several classic beamforming algorithms to take advantage of echoes and also propose new optimal formulations. We explore formulations both in time and frequency domains. We show theoretically and in numerical simulations that the signal-to-interference-and-noise ratio increases proportionally to the number of echoes used. Finally, beyond objective measures, we show that echoes also directly improve speech intelligibility as measured by the perceptual evaluation of speech quality (PESQ) metric. Next, we attack the problem of direction of arrival of acoustic sources, to which we apply a robust finite rate of innovation reconstruction framework. FRIDA â the resulting algorithm â exploits wideband information coherently, works at very low signal-to-noise ratio, and can resolve very close sources. The algorithm can use either raw microphone signals or their cross- correlations. While the former lets us work with correlated sources, the latter creates a quadratic number of measurements that allows to locate many sources with few microphones. Thorough experiments on simulated and recorded data shows that FRIDA compares favorably with the state-of-the-art. We continue by revisiting the classic recursive least squares (RLS) adaptive filter with ideas borrowed from recent results on sketching least squares problems. The exact update of RLS is replaced by a few steps of conjugate gradient descent. We propose then two different precondi- tioners, obtained by sketching the data, to accelerate the convergence of the gradient descent. Experiments on artificial as well as natural signals show that the proposed algorithm has a performance very close to that of RLS at a lower computational burden. The fifth and final chapter is dedicated to the software and hardware tools developed for this thesis. We describe the pyroomacoustics Python package that contains routines for the evaluation of audio processing algorithms and reference implementations of popular algorithms. We then give an overview of the microphone arrays developed

A QUALITATIVE STUDY EXAMINING THE LITERACY EXPERIENCES OF MALE MIDDLE SCHOOL STUDENTS INSIDE AND OUTSIDE OF SCHOOL

A literacy gap is a difference between a person’s ability to read for understanding and meaning-making and their anticipated ability to read for their grade level. A larger proportion of males are at least one or more years below grade level in reading ability compared to their female peers. This reading difference is called the gender literacy gap. Students over one year below grade level are at an increased risk of dropping out of high school and face the possibility of diminished lifetime earnings. Gender, low levels of motivation, low socio-economic status, low engagement, and school perceptions of literacy are risk factors present in the literature. Middle school male students did not recognize how they used literacy outside the classroom as they interacted with literacy differently outside and inside the classroom. Out of the classroom, male middle school students used digital platforms such as Google, YouTube, and WhatsApp to learn about topics of authentic or personal interest. Physical media, such as textbooks, were referenced inside the classroom to complete teacher-assigned tasks. Data showed a significant preference for peer support outside and inside the classroom. However, inside the classroom, when the textbooks proved unsatisfactory, the students reached out to the teacher for assistance. This misalignment between how students learn produces adverse outcomes for male middle school students