Virtual three-dimensional (3D) auditory displays utilize signal-processing techniques to alter sounds presented through headphones so that they seem to originate from specific spatial locations around the listener. In some circumstances bone-conduction headsets (bonephones) can provide an alternative sound presentation mechanism. However, existing 3D audio rendering algorithms need to be adjusted to use bonephones rather than headphones. This study provided anchor points for a function of shift values that could be used to adapt virtual 3D auditory displays for use with bonephones. The shift values were established by having participants adjust phase and amplitude of two waves in order to cancel out the signal and thus produce silence. These adjustments occurred in a listening environment consisting of air-conducted and bone-conducted tones, as well as air- conducted masking. Performance in the calibration condition suggested that participants understood the task, and could do this task with reasonable accuracy. In the bone-to-air listening conditions, the data produced a clear set of anchor points for an amplitude shift function. The data did not reveal, however, anchor points for a phase shift function the data for phase were highly variable and inconsistent. Application of shifts, as well as future research to establish full functions and better understand phase are discussed, in addition to validation and follow-up studies.

The objective of this research is to develop a bearing fault detection scheme for electric machines via stator current. A new method, called the stator current noise cancellation method, is proposed to separate bearing fault-related components in the stator current. This method is based on the concept of viewing all bearing-unrelated components as noise and defining the bearing detection problem as a low signal-to-noise ratio (SNR) problem. In this method, a noise cancellation algorithm based on Wiener filtering is employed to solve the problem. Furthermore, a statistical method is proposed to process the data of noise-cancelled stator current, which enables bearing conditions to be evaluated solely based on stator current measurements. A detailed theoretical analysis of the proposed methods is presented. Several online tests are also performed in this research to validate the proposed methods. It is shown in this work that a bearing fault can be detected by measuring the variation of the RMS of noise-cancelled stator current by using statistical methods such as the Statistical Process Control. In contrast to most existing current monitoring techniques, the detection methods proposed in this research are designed to detect generalized-roughness bearing faults. In addition, the information about machine parameters and bearing dimensions are not required in the implementation.

Orthogonal frequency division multiplexing (OFDM) is the major technique for next generation wireless communication system because of its high spectral efficiency. In addition, multiple-input multiple-output (MIMO) technique is usually used to further increase system capacity. There are two major coding schemes adopted in MIMO-OFDM systems, i.e. space-time block code (STBC) and space-frequency block code (SFBC). This thesis investigates the orthogonal-space-frequency block code OFDM (OSFBC-OFDM) system. In SFBC-OFDM systems, the channel frequency response is usually assumed to be the same for adjacent subcarriers. However, this assumption is not valid in frequency-selective fading environment. Therefore, the orthogonality of code structure is destroyed, leading to substantial increase in interference and significant decrease in system performance. This thesis proposes a receiver equalizer which adopts an interference cancellation (IC) mechanism to maximize the signal to interference plus noise ratio (SINR). Both the Lagrange multiplier method and eigenvalue method are adopted in the interference cancellation. Simulation experiments are conducted to verify the system performance and results demonstrate that the SINR performance is dramatically improved.

The cyclic prefix (CP) is usually adopted in single carrier frequency domain equalization (SC-FDE) system to avoid inter-block interference (IBI) and inter-symbol interference (ISI) in multipath fading channels. In addition, the use of CP also converts the linear convolution between the transmitted signal and the channel into a circular convolution, leading to significant decrease in receiver equalization. However, the use of CP reduces the bandwidth efficiency. Therefore the SC-FDE system without CP is investigated in this thesis. A number of schemes have been proposed to improve the performance of systems without CP, where both IBI and ICI are dramatically increased. Unfortunately, most of the existing schemes have extremely high computational complexity and are difficult to realize. In this thesis, a novel low-complexity CP reconstruction (CPR) scheme is proposed for interference cancellation, where the successive interference cancellation (SIC) and QR decomposition (QRD) are adopted. In addition, the system performance is further improved by using the fact that the interferences of different symbols are not the same. Simulation experiments are conducted to verify the system performance of the proposed scheme. It is shown that the proposed scheme can effectively reduce the interference, while maintain a low computational complexity.

This dissertation is aimed at examining signal integrity degradation factors and realizing signal integrity enhancement circuits for both wired and wireless communication systems. For wired communication systems, an optical coherent system employing an electrical equalization circuit is studied as a way of extending the transmission distance limited by optical fiber dispersion mechanisms. System simulation of the optical coherent receiver combined with the feed-forward equalizers is performed to determine the design specification of the equalizer circuit. The equalization circuit is designed and implemented in a 0.18 µm complementary metal-oxide semiconductor (CMOS) process and demonstrates the capability to extend the transmission reach of long-haul optical systems over single-mode fiber to 600 km. Additionally, for wireless applications, signal integrity issues found in a full-duplex wireless communication network are examined. Full-duplex wireless systems are subject to interference from their own transmitter leakage signals; thus, a transmitter leakage cancellation circuit is designed and implemented in a 0.18 µm CMOS technology. The proposed cancellation circuit is integrated with a low-noise amplifier and demonstrates over 20 dB of transmitter leakage signal suppression.

Under a number of practical operating scenarios, traditional moving target indicator (MTI) systems inadequately suppress ground clutter in airborne radar systems. Due to the moving platform, the clutter gains a nonzero relative velocity and spreads the power across Doppler frequencies. This obfuscates slow-moving targets of interest near the "direct current" component of the spectrum. In response, space-time adaptive processing (STAP) techniques have been developed that simultaneously operate in the space and time dimensions for effective clutter cancellation. STAP algorithms commonly operate under the assumption of homogeneous clutter, where the returns are described by complex, white Gaussian distributions. Empirical evidence shows that this assumption is invalid for many radar systems of interest, including high-resolution radar and radars operating at low grazing angles. We are interested in these heterogeneous cases, i.e., cases when the Gaussian model no longer suffices. Hence, the development of reliable STAP algorithms for real systems depends on the accuracy of the heterogeneous clutter models. The clutter of interest in this work includes heterogeneous texture clutter and point clutter. We have developed a cell-based clutter model (CCM) that provides simple, yet faithful means to simulate clutter scenarios for algorithm testing. The scene generated by the CMM can be tuned with two parameters, essentially describing the spikiness of the clutter scene. In one extreme, the texture resembles point clutter, generating strong returns from localized range-azimuth bins. On the other hand, our model can also simulate a flat, homogeneous environment. We prove the importance of model-based STAP techniques, namely knowledge-aided parametric covariance estimation (KAPE), in filtering a gamut of heterogeneous texture scenes. We demonstrate that the efficacy of KAPE does not diminish in the presence of typical spiky clutter. Computational complexities and susceptibility to modeling errors prohibit the use of KAPE in real systems. The computational complexity is a major concern, as the standard KAPE algorithm requires the inversion of an MNxMN matrix for each range bin, where M and N are the number of array elements and the number of pulses of the radar system, respectively. We developed a Gram Schmidt (GS) KAPE method that circumvents the need of a direct inversion and reduces the number of required power estimates. Another unavoidable concern is the performance degradations arising from uncalibrated array errors. This problem is exacerbated in KAPE, as it is a model-based technique; mismatched element amplitudes and phase errors amount to a modeling mismatch. We have developed the power-ridge aligning (PRA) calibration technique, a novel iterative gradient descent algorithm that outperforms current methods. We demonstrate the vast improvements attained using a combination of GS KAPE and PRA over the standard KAPE algorithm under various clutter scenarios in the presence of array errors.

To reduce cost, many digital cameras use a single sensor array instead of using three arrays for the red, green and blue. Thus at each pixel location only the red, green or blue intensity value is available. And to generate a complete color image, the camera must estimate the missing two values at each pixel location .Color filter arrays are used to capture only one portion of the spectrum (Red, Green or Blue) at each location. Various arrangements of the Color Filter Array (CFA) are possible, but the Bayer array is the most commonly used arrangement and we will deal exclusively with the Bayer array in this thesis. Since each of the three colors channels are effectively downsampled, it leads to aliasing artifacts. This thesis will analyze the effects of aliasing in the frequency- domain and present a method to reduce the deterioration in image quality due to aliasing artifacts. Two reference algorithms, AH-POCS (Adams and Hamilton - Projection Onto Convex Sets) and Adaptive Homogeneity-Directed interpolation, are discussed in de- tail. Both algorithms use the assumption that there is high correlation in the high- frequency regions to reduce aliasing. AH-POCS uses alias cancellation technique to reduce aliasing in the red and blue images, while the Adaptive Homogeneity-Directed interpolation algorithm is an edge-directed algorithm. We present here an algorithm that combines these two techniques and provides a better result on average when compared to the reference algorithms.

The objective of this research is to presents new acoustic echo cancellation design methods that can effectively work in the nonlinear environment. Acoustic echo is an annoying issue for voice communication systems. Because of room acoustics and delay in the transmission path, echoes affect the sound quality and may hamper communications. Acoustic echo cancellers (AECs) are employed to remove the acoustic echo while keeping full-duplex communications. AEC designs face a variety of challenges, including long room impulse response, acoustic path nonlinearity, ambient noise, and double-talk situation. We investigate two parts of echo canceller design: echo cancellation algorithm design and control logic algorithm design. In the first part, our work focuses on the nonlinear adaptive and fast-convergence algorithms. We investigate three different structures: predistortion linearization, cascade structure, and nonlinear residual echo suppressor. Specifically, we are interested in the coherence function, since it provides a means for quantifying linear association between two stationary random processes. By using the coherence as a criterion to design the nonlinear echo canceller in the system, our method guarantees the algorithm stability and leads to a faster convergence rate. In the second part, our work focuses on the robustness of AECs in the presence of interference. With regard to the near-end speech, we investigate the double-talk detector (DTD) design in conjunction with nonlinear AECs. Specifically, we propose to design a DTD based on the mutual information (MI). We show that the advantage of the MI-based method, when compared with the existing methods, is that it is applicable to both the linear and nonlinear scenarios. With respect to the background noise, we propose a variable step-size and variable tap-length least mean square (LMS) algorithm. Based on the fact that the room impulse response usually exhibits an exponential decay power profile in acoustic echo cancellation applications, the proposed method finds optimal step size and tap length at each iteration. Thus, it achieves faster convergence rate and better steady-state performance. We show a number of experimental results to illustrate the performance of the proposed algorithms.

Workflow systems aim to provide automated support for the conduct of certain business processes. Workflow systems are driven by workflow specifications which among others, capture the execution interdependencies between various activities. These interdependencies are modelled by means of different control flow constructors, e.g., sequence, choice, parallelism and synchronisation. It has been shown in the research on workflow patterns that the support for and the interpretation of various control flow constructs varies substantially across workflow systems. Two of the most problematic patterns relate to the OR-join and to cancellation. An OR-join is used in situations when we need to model " wait and see" behaviour for synchronisation. Different approaches assign a different (often only intuitive) semantics to this type of join, though they do share the common theme that synchronisation is only to be performed for active paths. Depending on context assumptions this behaviour may be relatively easy to deal with, though in general its semantics is complicated, both from a definition point of view (in terms of formally capturing a desired intuitive semantics) and from a computational point of view (how does one determine whether an OR-join is enabled?). Many systems and languages struggle with the semantics and implementation of the OR-join because its non-local semantics require a synchronisation depending on an analysis of future execution paths. This may require some non-trivial reasoning. The presence of cancellation features and other OR-joins in a workflow further complicates the formal semantics of the OR-join. The cancellation feature is commonly used to model external events that can change the behaviour of a running workflow. It can be used to either disable activities in certain parts of a workflow or to stop currently running activities. Even though it is possible to cancel activities in workflow systems using some sort of abort function, many workflow systems do not provide direct support for this feature in the workflow language. Sometimes, cancellation affects only a selected part of a workflow and other activities can continue after performing a cancellation action. As cancellation occurs naturally in business scenarios, comprehensive support in a workflow language is desirable. We take on the challenge of providing formal semantics, verification techniques as well as an implementation for workflows with those features. This thesis addresses three interrelated issues for workflows with cancellation regions and OR-joins. The concept of the OR-join is examined in detail in the context of the workflow language YAWL, a powerful workflow language designed to support a collection of workflow patterns and inspired by Petri nets. The OR-join semantics has been redesigned to represent a general, formal, and decidable approach for workflows in the presence of cancellation regions and other OR-joins. This approach exploits a link that is proposed between YAWL and reset nets, a variant of Petri nets with a special type of arc that can remove all tokens from a place. Next, we explore verification techniques for workflows with cancellation regions and OR-joins. Four structural properties have been identified and a verification approach that exploits coverability and reachability notions from reset nets has been proposed. The work on verification techniques has highlighted potential problems with calculating state spaces for large workflows. Applying reduction rules before carrying out verification can decrease the size of the problem by cutting down the size of the workflow that needs to be examined while preserving some essential properties. Therefore, we have extended the work on verification by proposing reduction rules for reset nets and for YAWL nets with and without OR-joins. The proposed OR-join semantics as well as the proposed verification approach have been implemented in the YAWL environment.

Thesis (Master').