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 Title
 A waveletbased detector for underwater communication.
 Creator
 Petljanski, Branko., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
 Abstract/Description

The need for reliable underwater communication at Florida Atlantic University is critical in transmitting data to and from Autonomous Underwater Vehicles (AUV) and remote sensors. Since a received signal is corrupted with ambient ocean noise, the nature of such noise is investigated. Furthermore, we establish connection between ambient ocean noise and fractal noise. Since the matched filter is designed under the assumption that noise is white, performance degradation of the matched filter due...
Show moreThe need for reliable underwater communication at Florida Atlantic University is critical in transmitting data to and from Autonomous Underwater Vehicles (AUV) and remote sensors. Since a received signal is corrupted with ambient ocean noise, the nature of such noise is investigated. Furthermore, we establish connection between ambient ocean noise and fractal noise. Since the matched filter is designed under the assumption that noise is white, performance degradation of the matched filter due nonwhite noise is investigated. We show empirical results that the wavelet transform provides an approximate KarhunenLoeve expansion for 1/ftype noise. Since whitening can improve only broadband signals, a new method for synchronization signal design in wavelet subspaces with increased energytopeak amplitude ratio is presented. The wavelet detector with whitening of fractal noise and detection in wavelet subspace is shown. Results show that the wavelet detector improves detectability, however this is below expectation due to differences between fractal noise and ambient ocean noise.
Show less  Date Issued
 2001
 PURL
 http://purl.flvc.org/fcla/dt/12778
 Subject Headings
 Wavelets (Mathematics), Underwater acoustics
 Format
 Document (PDF)
 Title
 Subspace detection and scale evolutionary eigendecomposition.
 Creator
 Kyperountas, Spyros C., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
 Abstract/Description

A measure of the potential of a receiver for detection is detectability. Detectability is a function of the signal and noise, and given any one of them the detectability is fixed. In addition, complete transforms of the signal and noise cannot change detectability. Throughout this work we show that "Subspace methods" as defined here can improve detectability in specific subspaces, resulting in improved Receiver Operating Curves (ROC) and thus better detection in arbitrary noise environments....
Show moreA measure of the potential of a receiver for detection is detectability. Detectability is a function of the signal and noise, and given any one of them the detectability is fixed. In addition, complete transforms of the signal and noise cannot change detectability. Throughout this work we show that "Subspace methods" as defined here can improve detectability in specific subspaces, resulting in improved Receiver Operating Curves (ROC) and thus better detection in arbitrary noise environments. Our method is tested and verified on various signals and noises, both simulated and real. The optimum detection of signals in noise requires the computation of noise eigenvalues and vectors (EVD). This process neither is a trivial one nor is it computationally cheap, especially for nonstationary noise and can result in numerical instabilities when the covariance matrix is large. This work addresses this problem and provides solutions that take advantage of the subspace structure through plane rotations to improve on existing algorithms for EVD by improving their convergence rate and reducing their computational expense for given thresholds.
Show less  Date Issued
 2001
 PURL
 http://purl.flvc.org/fcla/dt/11965
 Subject Headings
 Eigenvalues, Eigenvectors, Wavelets (Mathematics)
 Format
 Document (PDF)
 Title
 Subband coding of images using binomial QMF and vector quantization.
 Creator
 Rajamani, Kannan., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
 Abstract/Description

This thesis presents an image coding system using binomial QMF based subband decomposition and vector quantisation. An attempt was made to compress a still image of size 256 x 256 represented at a resolution of 8 bits/pixel to a bit rate of 0.5 bits/pixel using 16 channel subband decomposition with binomial QMFs and coding the subbands using a full search LBG Vector Quantizer (VQ). Simulations were done on SUN work station and the quality of the image was evaluated by computing the Signal to...
Show moreThis thesis presents an image coding system using binomial QMF based subband decomposition and vector quantisation. An attempt was made to compress a still image of size 256 x 256 represented at a resolution of 8 bits/pixel to a bit rate of 0.5 bits/pixel using 16 channel subband decomposition with binomial QMFs and coding the subbands using a full search LBG Vector Quantizer (VQ). Simulations were done on SUN work station and the quality of the image was evaluated by computing the Signal to Noise Ratio (SNR) between the original image and the reconstructed image.
Show less  Date Issued
 1995
 PURL
 http://purl.flvc.org/fcla/dt/15203
 Subject Headings
 Image compressionDigital techniques, Image processingDigital techniques, Image transmissionDigital techniques, Coding theory, Vector fields
 Format
 Document (PDF)
 Title
 Timefrequency estimation for cyclostationary signals.
 Creator
 Frederick, Thomas James., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
 Abstract/Description

This thesis provides detailed analysis and design techniques for WignerVille spectrum (WVS) estimators for use with cyclostationary signals. The resulting class of estimators represent a newly defined subset of Cohen's class characterized by a mixed discretetime/continuousfrequency smoothing kernel. Although both timevariant and shift invariant versions of the estimator are developed, emphasis is placed on the shiftinvariant version which is designed to estimate the WVS over an entire...
Show moreThis thesis provides detailed analysis and design techniques for WignerVille spectrum (WVS) estimators for use with cyclostationary signals. The resulting class of estimators represent a newly defined subset of Cohen's class characterized by a mixed discretetime/continuousfrequency smoothing kernel. Although both timevariant and shift invariant versions of the estimator are developed, emphasis is placed on the shiftinvariant version which is designed to estimate the WVS over an entire period from a single observation. Bias and variance expressions are derived for the new estimator, and these are compared with the general estimator. For this development, we also derive mean and covariance expressions for the general quasistationary based estimators, both for the autocorrelation estimator and for the WVS estimator. The concept of quasistationarity is extended to cyclostationary models, and we develop a novel measure of kernel smoothing and variance reduction termed the timebandwidth area. This is a generalization of timebandwidth product to describe arbitrary kernel functions, even those which are not governed by the uncertainty principle (such as the newly proposed estimators). The properties of the estimator are examined in terms of constraints on the smoothing kernel. In sharp contrast to the conventional estimators based on the quasistationary assumption, the low bias and low variance constraints for the new class of estimators do not contradict one another. The relationship between time dependent spectral estimation for nonstationary processes and classical BlackmanTukey type spectral estimation for stationary processes is developed next. Using examples the utility of the new estimator kernels are shown. It is seen that in random or noisy environments it may be difficult to achieve a reasonable tradeoff between variance reduction and bias using conventional estimators. In the examples any assumption of quasistationarity sufficient to produce a low variance estimate would destroy many or all of the nonstationary features of the signal. However, since the signals are cyclostationary we can employ the new class of estimators to achieve an excellent balance between bias and variance reduction.
Show less  Date Issued
 1997
 PURL
 http://purl.flvc.org/fcla/dt/12537
 Subject Headings
 Signal processing, Wigner distribution
 Format
 Document (PDF)
 Title
 Concurrent linear predictive coding.
 Creator
 McLean, William Gregory., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
 Abstract/Description

This thesis describes a software model of a Linear Predictive Coding (L.P.C.) that is written in the Ada language. The novel feature of this program is that it attempts to execute the maximum possible number of concurrent arithmetic operations in the L.P.C. algorithm. Each arithmetic operation is implemented by an active process which is the "task" construct in the Ada language. The computational part of the algorithm is implemented as a wavefront array of computing tasks. These computational...
Show moreThis thesis describes a software model of a Linear Predictive Coding (L.P.C.) that is written in the Ada language. The novel feature of this program is that it attempts to execute the maximum possible number of concurrent arithmetic operations in the L.P.C. algorithm. Each arithmetic operation is implemented by an active process which is the "task" construct in the Ada language. The computational part of the algorithm is implemented as a wavefront array of computing tasks. These computational arrays are driven by a driver task which coordinates the flow of data into and out of the computing surfaces. If the inter process communications time between tasks is small, then this model shows a potential for speedup. If this be the case, one may conclude that this model is an appropriate implementation for a linear predictive coding.
Show less  Date Issued
 1989
 PURL
 http://purl.flvc.org/fcla/dt/14498
 Subject Headings
 Signal processingDigital techniques, Signal processing, Programming languages (Electronic computers)
 Format
 Document (PDF)
 Title
 The cochlea: A signal processing paradigm.
 Creator
 Barrett, Raymond L. Jr., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
 Abstract/Description

The cochlea provides frequency selectivity for acoustic input signal processing in mammals. The excellent performance of human hearing for speech processing leads to examination of the cochlea as a paradigm for signal processing. The components of the hearing process are examined and suitable models are selected for each component's function. The signal processing function is simulated by a computer program and the ensemble is examined for behavior and improvement. The models reveal that the...
Show moreThe cochlea provides frequency selectivity for acoustic input signal processing in mammals. The excellent performance of human hearing for speech processing leads to examination of the cochlea as a paradigm for signal processing. The components of the hearing process are examined and suitable models are selected for each component's function. The signal processing function is simulated by a computer program and the ensemble is examined for behavior and improvement. The models reveal that the motion of the basilar membrane provides a very selective low pass transmission characteristic. Narrowband frequency resolution is obtained from the motion by computation of spatial differences in the magnitude of the motion as energy propagates along the membrane. Basilar membrane motion is simulated using the integrable model of M. R. Schroeder, but the paradigm is useful for any model that exhibits similar high selectivity. Support is shown for an hypothesis that good frequency discrimination is possible without highly resonant structure. The nonlinear magnitude calculation is performed on signals developed without highly resonant structure, and differences in those magnitudes are signals shown to have good narrowband selectivity. Simultaneously, good transient behavior is preserved due to the avoidance of highly resonant structure. The cochlear paradigm is shown to provide a power spectrum with serendipitous good frequency selectivity and good transient response simultaneously.
Show less  Date Issued
 1990
 PURL
 http://purl.flvc.org/fcla/dt/12251
 Subject Headings
 Engineering, Electronics and Electrical, Computer Science
 Format
 Document (PDF)