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Array processing is an area of study devoted to processing the signals received from an antenna array and extracting information of interest. It has played an important role in widespread applications like radar, sonar, and wireless communications. Numerous adaptive array processing algorithms have been reported in the literature in the last several decades. These algorithms, in a general view, exhibit a trade-off between performance and required computational complexity. In this thesis, we focus on the development of array processing algorithms in the application of beamforming and direction of arrival (DOA) estimation. In the beamformer design, we employ the constrained minimum variance (CMV) and the constrained constant modulus (CCM) criteria to propose full-rank and reduced-rank adaptive algorithms. Specifically, for the full-rank algorithms, we present two low-complexity adaptive step size mechanisms with the CCM criterion for the step size adaptation of the stochastic gradient (SG) algorithms. The convergence and steady-state properties are analysed. Then, the full-rank constrained conjugate gradient (CG) adaptive filtering algorithms are proposed according to the CMV and CCM criteria. We introduce a CG based weight vector to incorporate the constraint in the design criteria for solving the system of equations that arises from each design problem. The proposed algorithms avoid the covariance matrix inversion and provide a trade-off between the complexity and performance. In reduced-rank array processing, we present CMV and CCM reduced-rank schemes based on joint iterative optimization (JIO) of adaptive filters. This scheme consists a bank of full-rank adaptive filters that forms the transformation matrix, and an adaptive reduced-rank filter that operates at the output of the bank of filters. The transformation matrix and the reduced-rank weight vector are jointly optimized according to the CMV or CCM criteria. For the application of beamforming, we describe the JIO scheme for both the direct-form processor (DFP) and the generalized sidelobe canceller (GSC) structures. For each structure, we derive SG and recursive least squares (RLS) type algorithms to iteratively compute the transformation matrix and the reduced-rank weight vector for the reduced-rank scheme. An auxiliary vector filtering (AVF) algorithm based on the CCM design for robust beamforming is presented. The proposed beamformer decomposes the adaptive filter into a constrained (reference vector filter) and an unconstrained (auxiliary vector filter) component. The weight vector is iterated by subtracting the scaling auxiliary vector from the reference vector. For the DOA estimation, the reduced-rank scheme with the minimum variance (MV) power spectral evaluation is introduced. A spatial smoothing (SS) technique is employed in the proposed method to improve the resolution. The proposed DOA estimation algorithms are suitable for large arrays and to deal with direction finding for a small number of snapshots, a large number of users, and without the exact information of the number of sources.

Computer-mediated communication (CMC) is increasingly used in higher education, but it is not without problems. The effectiveness of CMC depends on many factors, including the characteristics of CMC systems themselves. The research reported here therefore aimed to investigate how an educational CMC system might be improved, in order to support learning more effectively. The main context for the research was distance learning at the UK Open University (OU). A two-stage, mixed methods research approach was adopted. In the first stage, interviews and observations were carried out to explore the benefits and problems experienced by users. This revealed two major issues: information overload and lack of social presence. Information overload relates to users’ problems dealing with large numbers of messages. Social presence relates to the need for users to feel connected with each other. The second stage investigated system features aimed at addressing these issues, implemented in a prototype computer conferencing system. Features to address overload included branched message threading and user recommendations. Features to address social presence were ‘résumés’ and instant messaging. These features were evaluated using questionnaires, with several cohorts of students in an OU course. Students expressed approval of the features, although some features were not widely used. Students preferred branched threading to chronological threading because branching helped them to follow ‘conversations’. Students were uncomfortable recommending messages, feeling that the value of a message would vary between people. They were also uncomfortable using instant messaging to contact others whom they did not know. However, the awareness aspect of instant messaging provided a sense of solidarity. The research demonstrated that the problems of overload and lack of social presence are significant, and each has social aspects which must be addressed. Students’ relationships with each other affect whether and how they use the features of CMC systems. We can conclude that particular attention must be paid to the social aspects of online communication, both when designing educational CMC systems and when considering how they are used. To maximise the benefits for learning, students need to feel comfortable with each other online, and there are few short cuts to achieving this.