Thesis (M. Eng.)--Carleton University, 2004. / Includes bibliographical references (p. 141-145). Also available in electronic format on the Internet.

by Chi-Chiu Cheung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 124-131). / Abstract --- p.i / Acknowledgments --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Blind Signal Separation Problem --- p.1 / Chapter 1.2 --- Contributions of this Thesis --- p.3 / Chapter 1.3 --- Applications of the Problem --- p.4 / Chapter 1.4 --- Organization of the Thesis --- p.5 / Chapter 2 --- The Blind Signal Separation Problem --- p.7 / Chapter 2.1 --- The General Blind Signal Separation Problem --- p.7 / Chapter 2.2 --- Convolutive Linear Mixing Process --- p.8 / Chapter 2.3 --- Instantaneous Linear Mixing Process --- p.9 / Chapter 2.4 --- Problem Definition and Assumptions in this Thesis --- p.9 / Chapter 3 --- Literature Review --- p.13 / Chapter 3.1 --- Previous Works on Blind Signal Separation with Instantaneous Mixture --- p.13 / Chapter 3.1.1 --- Algebraic Approaches --- p.14 / Chapter 3.1.2 --- Neural approaches --- p.15 / Chapter 3.2 --- Previous Works on Blind Signal Separation with Convolutive Mixture --- p.20 / Chapter 4 --- The Information-theoretic ICA Scheme --- p.22 / Chapter 4.1 --- The Bayesian YING-YANG Learning Scheme --- p.22 / Chapter 4.2 --- The Information-theoretic ICA Scheme --- p.25 / Chapter 4.2.1 --- Derivation of the cost function from YING-YANG Machine --- p.25 / Chapter 4.2.2 --- Connections to previous information-theoretic approaches --- p.26 / Chapter 4.2.3 --- Derivation of the Algorithms --- p.27 / Chapter 4.2.4 --- Roles and Constraints on the Nonlinearities --- p.30 / Chapter 4.3 --- Direction and Motivation for the Analysis of the Nonlinearity --- p.30 / Chapter 5 --- Properties of the Cost Function and the Algorithms --- p.32 / Chapter 5.1 --- Lemmas and Corollaries --- p.32 / Chapter 5.1.1 --- Singularity of J(V) --- p.33 / Chapter 5.1.2 --- Continuity of J(V) --- p.34 / Chapter 5.1.3 --- Behavior of J(V) along a radially outward line --- p.35 / Chapter 5.1.4 --- Impossibility of divergence of the information-theoretic ICA al- gorithms with a large class of nonlinearities --- p.36 / Chapter 5.1.5 --- Number and stability of correct solutions in the 2-channel case --- p.37 / Chapter 5.1.6 --- Scale for the equilibrium points --- p.39 / Chapter 5.1.7 --- Absence of local maximum of J(V) --- p.43 / Chapter 6 --- The Algorithms with Cubic Nonlinearity --- p.44 / Chapter 6.1 --- The Cubic Nonlinearity --- p.44 / Chapter 6.2 --- Theoretical Results on the 2-Channel Case --- p.46 / Chapter 6.2.1 --- Equilibrium points --- p.46 / Chapter 6.2.2 --- Stability of the equilibrium points --- p.49 / Chapter 6.2.3 --- An alternative proof for the stability of the equilibrium points --- p.50 / Chapter 6.2.4 --- Convergence Analysis --- p.52 / Chapter 6.3 --- Experiments on the 2-Channel Case --- p.53 / Chapter 6.3.1 --- Experiments on two sub-Gaussian sources --- p.54 / Chapter 6.3.2 --- Experiments on two super-Gaussian sources --- p.55 / Chapter 6.3.3 --- Experiments on one super-Gaussian source and one sub-Gaussian source which are globally sub-Gaussian --- p.57 / Chapter 6.3.4 --- Experiments on one super-Gaussian source and one sub-Gaussian source which are globally super-Gaussian --- p.59 / Chapter 6.3.5 --- Experiments on asymmetric exponentially distributed signals .。 --- p.60 / Chapter 6.3.6 --- Demonstration on exactly and nearly singular initial points --- p.61 / Chapter 6.4 --- Theoretical Results on the 3-Channel Case --- p.63 / Chapter 6.4.1 --- Equilibrium points --- p.63 / Chapter 6.4.2 --- Stability --- p.66 / Chapter 6.5 --- Experiments on the 3-Channel Case --- p.66 / Chapter 6.5.1 --- Experiments on three pairwise globally sub-Gaussian sources --- p.67 / Chapter 6.5.2 --- Experiments on three sources consisting of globally sub-Gaussian and globally super-Gaussian pairs --- p.67 / Chapter 6.5.3 --- Experiments on three pairwise globally super-Gaussian sources --- p.69 / Chapter 7 --- Nonlinearity and Separation Capability --- p.71 / Chapter 7.1 --- Theoretical Argument --- p.71 / Chapter 7.1.1 --- Nonlinearities that strictly match the source distribution --- p.72 / Chapter 7.1.2 --- Nonlinearities that loosely match the source distribution --- p.72 / Chapter 7.2 --- Experiment Verification --- p.76 / Chapter 7.2.1 --- Experiments on reversed sigmoid --- p.76 / Chapter 7.2.2 --- Experiments on the cubic root nonlinearity --- p.77 / Chapter 7.2.3 --- Experimental verification of Theorem 2 --- p.77 / Chapter 7.2.4 --- Experiments on the MMI algorithm --- p.78 / Chapter 8 --- Implementation with Mixture of Densities --- p.80 / Chapter 8.1 --- Implementation of the Information-theoretic ICA scheme with Mixture of Densities --- p.80 / Chapter 8.1.1 --- The mixture of densities --- p.81 / Chapter 8.1.2 --- Derivation of the algorithms --- p.82 / Chapter 8.2 --- Experimental Verification on the Nonlinearity Adaptation --- p.84 / Chapter 8.2.1 --- Experiment 1: Two channels of sub-Gaussian sources --- p.84 / Chapter 8.2.2 --- Experiment 2: Two channels of super-Gaussian sources --- p.85 / Chapter 8.2.3 --- Experiment 3: Three channels of different signals --- p.89 / Chapter 8.3 --- Seeking the Simplest Workable Mixtures of Densities ......... .。 --- p.91 / Chapter 8.3.1 --- Number of components --- p.91 / Chapter 8.3.2 --- Mixture of two densities with only biases changeable --- p.93 / Chapter 9 --- ICA with Non-Kullback Cost Function --- p.97 / Chapter 9.1 --- Derivation of ICA Algorithms from Non-Kullback Separation Functionals --- p.97 / Chapter 9.1.1 --- Positive Convex Divergence --- p.97 / Chapter 9.1.2 --- Lp Divergence --- p.100 / Chapter 9.1.3 --- De-correlation Index --- p.102 / Chapter 9.2 --- Experiments on the ICA Algorithm Based on Positive Convex Divergence --- p.103 / Chapter 9.2.1 --- Experiments on the algorithm with fixed nonlinearities --- p.103 / Chapter 9.2.2 --- Experiments on the algorithm with mixture of densities --- p.106 / Chapter 10 --- Conclusions --- p.107 / Chapter A --- Proof for Stability of the Equilibrium Points of the Algorithm with Cubic Nonlinearity on Two Channels of Signals --- p.110 / Chapter A.1 --- Stability of Solution Group A --- p.110 / Chapter A.2 --- Stability of Solution Group B --- p.111 / Chapter B --- Proof for Stability of the Equilibrium Points of the Algorithm with Cubic Nonlinearity on Three Channels of Signals --- p.119 / Chapter C --- Proof for Theorem2 --- p.122 / Bibliography --- p.124

It is necessary for radars to suppress interferences to near the noise level to achieve the best performance in target detection and measurements. In this dissertation work, innovative signal processing approaches are proposed to effectively mitigate two of the most common types of interferences: jammers and clutter. Two types of radar systems are considered for developing new signal processing algorithms: phased-array radar and multiple-input multiple-output (MIMO) radar. For phased-array radar, an innovative target-clutter feature-based recognition approach termed as Beam-Doppler Image Feature Recognition (BDIFR) is proposed to detect moving targets in inhomogeneous clutter. Moreover, a new ground moving target detection algorithm is proposed for airborne radar. The essence of this algorithm is to compensate for the ground clutter Doppler shift caused by the moving platform and then to cancel the Doppler-compensated clutter using MTI filters that are commonly used in ground-based radar systems. Without the need of clutter estimation, the new algorithms outperform the conventional Space-Time Adaptive Processing (STAP) algorithm in ground moving target detection in inhomogeneous clutter. For MIMO radar, a time-efficient reduced-dimensional clutter suppression algorithm termed as Reduced-dimension Space-time Adaptive Processing (RSTAP) is proposed to minimize the number of the training samples required for clutter estimation. To deal with highly heterogeneous clutter more effectively, we also proposed a robust deterministic STAP algorithm operating on snapshot-to-snapshot basis. For cancelling jammers in the radar mainlobe direction, an innovative jamming elimination approach is proposed based on coherent MIMO radar adaptive beamforming. When combined with mutual information (MI) based cognitive radar transmit waveform design, this new approach can be used to enable spectrum sharing effectively between radar and wireless communication systems. The proposed interference mitigation approaches are validated by carrying out simulations for typical radar operation scenarios. The advantages of the proposed interference mitigation methods over the existing signal processing techniques are demonstrated both analytically and empirically.

The intense requirements for high processing rates of multidimensional Digital Signal Processing systems in practical applications justify the Application Specific Integrated Circuits designs and parallel processing implementations. In this dissertation, we propose novel theories, methodologies and architectures in designing high-performance VLSI implementations for general multidimensional multirate Digital Signal Processing systems by exploiting the parallelism within those applications. To systematically exploit the parallelism within the multidimensional multirate DSP algorithms, we develop novel transformations including (1) nonlinear I/O data space transforms, (2) intercalation transforms, and (3) multidimensional multirate unfolding transforms. These transformations are applied to the algorithms leading to systematic methodologies in high-performance architectural designs. With the novel design methodologies, we develop several architectures with parallel and distributed processing features for implementing multidimensional multirate applications. Experimental results have shown that those architectures are much more efficient in terms of execution time and/or hardware cost compared with existing hardware implementations.

Frequency estimation has been studied for a large number of years. One reason for this is that the problem is easy to understand, but difficult to solve. Another reason, for sure, is the large number of applications that involve frequency estimation, e.g radar using frequency modulated continuous wave (FMCW) techniques where the distance to the target is embedded in the frequency, resonance sensor systems where the output signal is given as the frequency displacement from a nominal frequency, radio frequency identification systems (RFID) where frequency modulation is used in the communication link, etc. The requirement on the frequency estimator varies with the application and typical issues include: accuracy, precision or (bias) processing speed or complexity, and ability to handle multiple signals. A lot of solutions to different problems in this area has been proposed, but still several open questions remain. The first part of this thesis addresses the problem of frequency estimation using low complexity algorithms. One way of achieving such an algorithm is to employ a coarse quantization on the input signal. In this thesis, a 1-bit quantizer is considered which enables the use of low complexity algorithms. Frequency estimation using look-up tables is studied and the properties of such an estimator are presented. By analyzing the look-up tables using the Hadamard transform a novel type of lowcomplexity frequency estimators is proposed. They use operations such as binary multiplication and addition of precalculated constants. This fact makes them suitable in applications where low complexity and high speed are major issues. A hardware demonstrator using the table look-up technique is designed and a prototype is analysed by real measurements. Today, the interest of using digital signal processing instead of analog processing is almost absolute. For example, in testing analog-to-digital converters an important part is to fit a sinewave to the recorded data, as well as to calculate the parameters that in least-squares sense result in the best fit. In this thesis, the sinewave fitting method included in the IEEE Standard 1057 is studied in some detail. Asymptotic Cramér-Rao bounds for three- and four model parameters are derived under the Gaussian assumption. Further, the sinewave fitting properties of the algorithm are analyzed by the parsimony principle. A novel model order selection criterion is proposed for waveform fitting methods in the case of a linear signal model. A generalization of this criterion is made to include the non-linear sinewave fitting application. For multiple sinewave fitting applications two iterative algorithms are proposed. The first method is a combination of the standardized sinewave fit algorithm and the expectation maximization algorithm. The second algorithm is an extension of a single sinewave model to a multiple sinewave model employing the standardized sinewave fitting algorithm. Both algorithms are analysed by numerical means and are shown to accurately resolve multiple sinewaves and produce efficient estimates. Initialization issues of such algorithms are included to some extent. / QC 20100830

The intense requirements for high processing rates of multidimensional Digital Signal Processing systems in practical applications justify the Application Specific Integrated Circuits designs and parallel processing implementations. In this dissertation, we propose novel theories, methodologies and architectures in designing high-performance VLSI implementations for general multidimensional multirate Digital Signal Processing systems by exploiting the parallelism within those applications. To systematically exploit the parallelism within the multidimensional multirate DSP algorithms, we develop novel transformations including (1) nonlinear I/O data space transforms, (2) intercalation transforms, and (3) multidimensional multirate unfolding transforms. These transformations are applied to the algorithms leading to systematic methodologies in high-performance architectural designs. With the novel design methodologies, we develop several architectures with parallel and distributed processing features for implementing multidimensional multirate applications. Experimental results have shown that those architectures are much more efficient in terms of execution time and/or hardware cost compared with existing hardware implementations.

Thesis (Ph.D.)--University of Wollongong, 2005. / Typescript. Includes bibliographical references: leaf 159-168.

Thesis (M. App. Sc.)--Carleton University, 2005. / Includes bibliographical references (p. 110-114). Also available in electronic format on the Internet.

Thesis (Ph. D.)--OGI School of Science & Engineering at OHSU, 2002.

Thesis (M.E.)--University of Canterbury, 2006. / Typescript (photocopy). "November 2006." Includes bibliographical references (p. [137]-142). Also available via the World Wide Web.