<p>This thesis addresses the problem of source localization and time-varying spatial spectrum estimation with maneuverable arrays. Two applications, each having different environmental assumptions and array geometries, are considered: 1) passive broadband source localization with a rigid 2-sensor array in a shallow water, multipath environment and 2) time-varying spatial spectrum estimation with a large, flexible towed array. Although both applications differ, the processing scheme associated with each is designed to exploit array maneuverability for improved localization and detection performance.</p><p>In the first application considered, passive broadband source localization is accomplished via time delay estimation (TDE). Conventional TDE methods, such as the generalized cross-correlation (GCC) method, make the assumption of a direct-path signal model and thus suffer localization performance loss in shallow water, multipath environments. Correlated multipath returns can result in spurious peaks in GCC outputs resulting in large bearing estimate errors. A new algorithm that exploits array maneuverability is presented here. The multiple orientation geometric averaging (MOGA) technique geometrically averages cross-correlation outputs to obtain a multipath-robust TDE. A broadband multipath simulation is presented and results indicate that the MOGA effectively suppresses correlated multipath returns in the TDE.</p><p>The second application addresses the problem of field directionality mapping (FDM) or spatial spectrum estimation in dynamic environments with a maneuverable towed acoustic array. Array processing algorithms for towed arrays are typically designed assuming the array is straight, and are thus degraded during tow ship maneuvers. In this thesis, maneuvering the array is treated as a feature allowing for left and right disambiguation as well as improved resolution towards endfire. The Cramer Rao lower bound is used to motivate the improvement in source localization which can be theoretically achieved by exploiting array maneuverability. Two methods for estimating time-varying field directionality with a maneuvering array are presented: 1) maximum likelihood estimation solved using the expectation maximization (EM) algorithm and 2) a non-negative least squares (NNLS) approach. The NNLS method is designed to compute the field directionality from beamformed power outputs, while the ML algorithm uses raw sensor data. A multi-source simulation is used to illustrate both the proposed algorithms' ability to suppress ambiguous towed-array backlobes and resolve closely spaced interferers near endfire which pose challenges for conventional beamforming approaches especially during array maneuvers. Receiver operating characteristics (ROCs) are presented to evaluate the algorithms' detection performance versus SNR. Results indicate that both FDM algorithms offer the potential to provide superior detection performance in the presence of noise and interfering backlobes when compared to conventional beamforming with a maneuverable array.</p> / Dissertation

Carbon dioxide (CO2) is the most important component of Greenhouse Gas (GHG) that causes global warming and sea-level rising. Thermal power plants dominate electric power generation in the world, and has been reported to be the major contributor of CO2 emission. To prevent the related global warming caused by GHG emission, carbon quota trading is implemented and becomes a gradually arising market. This thesis proposed a research focused on the relationship between the carbon trading scheme and dynamic economic dispatch (DED) problem for the public utility. A model of the carbon trading market was investigated and introduced into DED problem incorporating wind and solar power plant. A refined particle swarm optimization (PSO) algorithm, PSO with time-varying acceleration coefficients (PSO-TVAC), is applied to determine the DED strategy with the incorporation of independent power providers (IPPs) and green power plant. The model of the carbon trading was considered in the DED problem. Carbon reduction is treated as the inner-cost of utility, and the fictitious carbon quotas can be resold to the market, while the energy shortage can be satisfied by purchasing quotas from the market. In order to avoid premature convergence of the original PSO, the PSO-TVAC method is introduced to improve the searching efficiency.

According to Kim and Nelson (1999) and McConnell and Perez-Quiros (2000), the timing of the Great Moderation occurred in U.S. at 1984Q1. Summers (2005) found out several reasons and different timings of the Great Moderation in the G-7 countries and Australia. During the past fifty years, there was a significantly sharp decline in the volatility of the real growth rate in Australia. Between 1968 and 1982, the standard deviation of the real growth rate was 1.416%¡Fhowever, between 1983 and 1996, the standard deviation of the real growth rate drastically reduced to 0.917%. Based on this obvious situation described above, we successively build up a Markov-Switching Model and Time-Varying Structural Autoregressive Model to investigate the structural break and the sources of the Great Moderation in Australia. The findings turn out that improved monetary policy and the decreased oil shock can account for the explanation of the moderation with the break date of 1984Q1.

In this thesis, mathematical modeling and heuristic approaches are developed for surface-to-air weapon-target allocation problem with time varying single shot hit probabilities (SSHP) against linearly approaching threats. First, a nonlinear mathematical model for the problem is formulated to maximize sum of the weighted survival probabilities of assets to be defended. Next, nonlinear objective function and constraints are linearized. Time varying SSHP values are approximated with appropriate closed forms and adapted to the linear model obtained. This model is tested on different scenarios and results are compared with those of the original nonlinear model. It is observed that the linear model is solved much faster than the nonlinear model and produces reasonably good solutions. It is inferred from the solutions of both models that engagements should be made as late as possible, when the threats are closer to the weapons, to have SSHP values higher. A construction heuristic is developed based on this scheme. An improvement heuristic that uses the solution of the construction heuristic is also proposed. Finally, all methods are tested on forty defense scenarios. Two fastest solution methods, the linear model and the construction heuristic, are compared on a large scenario and proposed as appropriate solution techniques for the weapon-target allocation problems.

This thesis presents a comparison between two transmit diversity schemes, namely space-time coding and time-switched transmit diversity (TSTD) over block-fading and time-varying multi-input single-output (MISO) channels with different channel parameters. The schemes are concatenated with outer channel codes in order to achieve spatio-temporal diversity. The analytical results are derived for the error performances of the systems and the simulation results as well as outage probabilities are provided. Besides, the details of the pilot-symbol-aided modulation (PSAM) technique are investigated and the error performances of the systems are analyzed when the channel state information is estimated with PSAM. It is demonstrated using the analytical and simulation results that TSTD have a comparable error performance with the space-time coding techniques and it even outperforms the space-time codes for some channel parameters. Our results indicate that TSTD can be suggested as an alternative to space-time codes in some time-varying channels especially due to the implementation simplicity.

Orthogonal Frequency Division Multiplexing (OFDM) techniques have been used in many wireless communication systems to improve the system capacity and achieve high data-rate. It possesses good spectral efficiency and robustness against interferences. The OFDM system has been adopted in many communication standards, such as the 802.11a/g standards for the high-speed WLAN, HIPERLAN2, and IEEE 802.16 standard, and meanwhile, it is also employed in the European DAB and DVB systems. To avoid the inter-block interference (IBI), usually, in the transmitter of OFDM systems the redundancy with sufficient length is introduced, it allows us to overcome the IBI problem, due to highly dispersive channel. Many redundancy insertion methods have been proposed in the literatures, there are cyclic prefix (CP), zero padding (ZP) and the pseudorandom postfix (PRP). Under such system we have still to know the correct channel state information for equalizing the noisy block signal. Especially, in time-varying channel, the incorrect channel state information may introduce serious inter-symbol interference (ISI), if the channel estimation could not perform correctly. In this thesis, the PRP-OFDM system is considered. According to the PRP-OFDM scheme, the redundancy with pseudorandom postfix (PRP) approach is employed to make semi-blind channel estimation with order-one statistics of the received signal. But these statistic characteristics may not be available under time-varying channel. Hence, in this thesis, we propose a modified PRP-OFDM system with assistant training sequences, which is equipped with minimum mean-square-error equalizer and utilize Kalman filter algorithm to implement time-varying channel estimation. To do so, we first model time-varying channel estimation problem with a dynamic system, and adopt the Kalman filter algorithm to estimate the true channel coefficients. Unfortunately, since most parameters in dynamic system are random and could not to be known in advance. We need to apply effective estimation schemes to estimate the statistics of true parameters for implementing the Kalman filter algorithm. When the channel state information is known, MMSE equalizer follows to suppress the inter-symbol interference (ISI). Moreover, after making decision the binary data can be used to re-modulate PRP-OFDM symbol and to be re-used in Kalman filter to obtain more accurate CSI to improve the effectiveness of the equalizer. Via computer simulations, we verify that desired performance in terms of bit error rate (BER), can be achieved compared with the CP-OFDM systems.

To understand the processes affecting the abundance of wild populations is a fundamental goal of ecology and a prerequisite for the management of living resources. Variable abundance, however, makes the investigation of ecological processes challenging. Recruitment, the process whereby new individuals enter a given stage of a ?sh population, is a highly variable entity. I have confronted this issue by developing methodologies speci?cally designed to account for, and ecologically interpret, patterns of variability in recruitment. To provide the necessary context, Chapter 2 begins with a review of the history of recruitment science. I focus on the major achievements as well as present limitations, particularly regarding environmental drivers. Approaches that include explicit environmental information are contrasted with time-varying parameter techniques. In Chapter 3, I ask what patterns of variability in pre-recruit survival can tell us about the strength of density-dependent mortality. I provide methods to investigate the presence of density-dependent mortality where this has previously been hindered by highly variable data. Stochastic density-independent variability is found to be attenuated via density dependence. Sources of recruitment variability are further partitioned in Chapter 4. Using time-varying parameter techniques, signi?cant temporal variation in the annual reproductive rate is found to have occurred in many Atlantic cod populations. Multivariate state space models suggest that populations in close proximity typically have a shared response to environmental change whereas marked differences occur across latitude. Hypotheses that could result in consistent changes in productivity of cod populations are tested in Chapter 5. I focus on a meta-analytical investigation of potential interactions between Atlantic cod and small pelagic species, testing aspects of the cultivation-depensation hypothesis. The ?ndings suggest that predation or competition by herring and mackerel on egg and larval cod could delay recovery of depleted cod populations. Chapter 6 concludes with a critical re?ection on: the suitability of the theories employed, the underlying assumptions of the empirical approaches, and the quality of the data used in my thesis. Application of ecological insights to ?sheries management is critically evaluated. I then propose future work on recruitment processes based on methods presented herein.

Networked haptic cooperation entails direct interactions among the networked users in addition to joint manipulations of shared virtual objects. For example, therapists may want to feel and guide the motions of their remote patients directly rather than via an intervening virtual object during tele-rehabilitation sessions. To support direct user-to-user haptic interaction over a network, this dissertation introduces the concept of remote dynamic proxies and integrates it into two distributed control architectures. The remote dynamic proxies are avatars of users at the sites of their distant peers. They have second order dynamics and their motion is coordinated to the remote user whom they represent either via virtual coupling or via wave-based control. The remote dynamic proxies render smooth motion of the distant peers regardless of the infrequent and delayed information received over the network. Therefore, the integration of remote dynamic proxies into distributed networked haptic cooperation allows stiffer contacts to be rendered to users and improves position coherency in the presence of longer constant network delays. The thesis investigates the advantages and limitations of the remote dynamic proxies for two distributed haptic architectures. These architectures coordinate the peer users and their virtual environments via: - virtual coupling control. For virtual coupling-based networked haptics with remote dynamic proxies, stability is analyzed within a multi-rate state space framework and the analysis is validated through experiments involving both cooperative manipulations and direct user-to-user interactions. The results show that the remote dynamic proxies maintain high coherency between the distributed virtual environments and enable users to see and feel their peers moving smoothly. They also increase the stiffness of direct user-to-user contact in the presence of larger constant network delay. However, the remote dynamic proxies do not lessen users' perception of a predominantly viscous virtual environment in the presence of network delay. - wave-based control. To enable users to feel other dynamics in addition to viscosity during networked haptic cooperation, this dissertation further develops a wave-based distributed coordination approach for the remote dynamic proxies. The performance of the proposed approach is investigated via experiments involving both cooperative manipulations and direct user-to-user interactions. The results demonstrate that the remote dynamic proxies mitigate the poor coherency typical to wave-based coordination architectures and enable users to touch their peers. Furthermore, the remote dynamic proxies improve users' perception of inertia in the presence of network delay.

Doctor of Philosophy(PhD) / This thesis employs survival analysis framework (Allison, 1984) and the Cox’s hazard model (Cox, 1972) to estimate the probability that a credit rating survives in its current grade at a certain forecast horizon. The Cox’s hazard model resolves some significant drawbacks of the conventional estimation approaches. It allows a rigorous testing of non-Markovian behaviours and time heterogeneity in rating dynamics. It accounts for the changes in risk factors over time, and features the time structure of probability survival estimates. The thesis estimates three stratified Cox’s hazard models, including a proportional hazard model, and two dynamic hazard models which account for the changes in macro-economic conditions, and the passage of survival time over rating durations. The estimation of these stratified Cox’s hazard models for downgrades and upgrades offers improved understanding of the impact of rating history in a static and a dynamic estimation framework. The thesis overcomes the computational challenges involved in forming dynamic probability estimates when the standard proportionality assumption of Cox’s model does not hold and when the data sample includes multiple strata. It is found that the probability of rating migrations is a function of rating history and that rating history is more important than the current rating in determining the probability of a rating change. Switching from a static estimation framework to a dynamic estimation framework does not alter the effect of rating history on the rating migration hazard. It is also found that rating history and the current rating interact with time. As the rating duration extends, the main effects of rating history and current rating variables decay. Accounting for this decay has a substantial impact on the risk of rating transitions. Downgrades are more affected by rating history and time interactions than upgrades. To evaluate the predictive performance of rating history, the Brier score (Brier, 1950) and its covariance decomposition (Yates, 1982) were employed. Tests of forecast accuracy suggest that rating history has some predictive power for future rating changes. The findings suggest that an accurate forecast framework is more likely to be constructed if non-Markovian behaviours and time heterogeneity are incorporated into credit risk models.

abstract: Underwater acoustic communications face significant challenges unprecedented in radio terrestrial communications including long multipath delay spreads, strong Doppler effects, and stringent bandwidth requirements. Recently, multi-carrier communications based on orthogonal frequency division multiplexing (OFDM) have seen significant growth in underwater acoustic (UWA) communications, thanks to their well well-known robustness against severely time-dispersive channels. However, the performance of OFDM systems over UWA channels significantly deteriorates due to severe intercarrier interference (ICI) resulting from rapid time variations of the channel. With the motivation of developing enabling techniques for OFDM over UWA channels, the major contributions of this thesis include (1) two effective frequencydomain equalizers that provide general means to counteract the ICI; (2) a family of multiple-resampling receiver designs dealing with distortions caused by user and/or path specific Doppler scaling effects; (3) proposal of using orthogonal frequency division multiple access (OFDMA) as an effective multiple access scheme for UWA communications; (4) the capacity evaluation for single-resampling versus multiple-resampling receiver designs. All of the proposed receiver designs have been verified both through simulations and emulations based on data collected in real-life UWA communications experiments. Particularly, the frequency domain equalizers are shown to be effective with significantly reduced pilot overhead and offer robustness against Doppler and timing estimation errors. The multiple-resampling designs, where each branch is tasked with the Doppler distortion of different paths and/or users, overcome the disadvantages of the commonly-used single-resampling receivers and yield significant performance gains. Multiple-resampling receivers are also demonstrated to be necessary for UWA OFDMA systems. The unique design effectively mitigates interuser interference (IUI), opening up the possibility to exploit advanced user subcarrier assignment schemes. Finally, the benefits of the multiple-resampling receivers are further demonstrated through channel capacity evaluation results. / Dissertation/Thesis / Ph.D. Electrical Engineering 2011