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Title: An Algorithm for the Automated Interpretation of Cardiac Auscultation.
Creator: Lieber, Claude, Erdol, Nurgun, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Cardiac auscultation, an important part of the physical examination, is difficult for many primary care providers. As a result, diagnoses are missed or auscultatory signs misinterpreted. A reliable, automated means of interpreting cardiac auscultation should be of benefit to both the primary care provider and to patients. This paper explores a novel approach to this problem and develops an algorithm that can be expanded to include all the necessary electronics and programming to develop such...
Show moreCardiac auscultation, an important part of the physical examination, is difficult for many primary care providers. As a result, diagnoses are missed or auscultatory signs misinterpreted. A reliable, automated means of interpreting cardiac auscultation should be of benefit to both the primary care provider and to patients. This paper explores a novel approach to this problem and develops an algorithm that can be expanded to include all the necessary electronics and programming to develop such a device. The algorithm is explained and its shortcomings exposed. The potential for further development is also expounded.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004609, http://purl.flvc.org/fau/fd/FA00004609
Subject Headings: Phonocardiography., Signal processing., Pattern recognition systems., Imaging systems in medicine., Decision support systems., Medicine--Data processing.
Format: Document (PDF)

Title: APPLICATION OF LINE SPECTRUM PAIRS TO TONE DETECTION (SINEWAVE, FREQUENCIES, SINUSOIDAL, PREDICTIVE, AUTOCORRELATION).
Creator: WODKE, KENNETH E., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This thesis deals with the application of Line Spectrum Pairs to tone detection. Linear Predictive Coding (LPC) is described as a background to deriving the Line Spectrum Pairs. Two sources of LPC prediction coefficients are used to calcul?te Line Spectrum Pairs. One source is the polynomial roots of an LPC inverse filter; various locations of up to 3 pairs of complex conjugate roots are used to provide filter coefficients. The radii of the conjugate roots are varied to see the effect on the...
Show moreThis thesis deals with the application of Line Spectrum Pairs to tone detection. Linear Predictive Coding (LPC) is described as a background to deriving the Line Spectrum Pairs. Two sources of LPC prediction coefficients are used to calcul?te Line Spectrum Pairs. One source is the polynomial roots of an LPC inverse filter; various locations of up to 3 pairs of complex conjugate roots are used to provide filter coefficients. The radii of the conjugate roots are varied to see the effect on the calculated Line Spectrum Pairs. A second source of the filter coefficients is single and multiple sinusoidal tones that are LPC analyzed by the autocorrelation method to generate filter prediction coefficients. The frequencies and amplitudes of the summed sinusoids, and the length of the LPC analysis window are varied to determine the ability to detect the sinusoids by calculating the related Line Spectrum Pairs.
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Date Issued: 1986
PURL: http://purl.flvc.org/fcla/dt/14328
Subject Headings: Speech processing systems
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.
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Date Issued: 1990
PURL: http://purl.flvc.org/fcla/dt/12251
Subject Headings: Engineering, Electronics and Electrical, Computer Science
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 speed-up. If this be the case, one may conclude that this model is an appropriate implementation for a linear predictive coding.
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Date Issued: 1989
PURL: http://purl.flvc.org/fcla/dt/14498
Subject Headings: Signal processing--Digital techniques, Signal processing, Programming languages (Electronic computers)
Format: Document (PDF)

Title: Digital techniques for electronic countermeasures signal-processing.
Creator: Lopez, Juan J., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The purpose of this thesis is to show the use of digital techniques for Electronic Countermeasures (ECM) signal processing. The main objective is the use of only digital circuitry for the processing of the ECM signals. A recent design of an ECM controller called the Oscillator Waveform Controller (OWC) follows this philosophy. The OWC digitally controls the generation of its nine jamming modes plus the modes generated by the other ECM modules within the ECM system. The use of advance...
Show moreThe purpose of this thesis is to show the use of digital techniques for Electronic Countermeasures (ECM) signal processing. The main objective is the use of only digital circuitry for the processing of the ECM signals. A recent design of an ECM controller called the Oscillator Waveform Controller (OWC) follows this philosophy. The OWC digitally controls the generation of its nine jamming modes plus the modes generated by the other ECM modules within the ECM system. The use of advance microcircuitry technology allows the OWC the capability of controlling all the parameters within an ECM system. The most desirable feature of the OWC is the use of high level communications for programming ECM mode parameters from an external computer or terminal and digitally storing this parameters upon removal of power.
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Date Issued: 1987
PURL: http://purl.flvc.org/fcla/dt/14427
Subject Headings: Electronic countermeasures, Signal processing--Digital techniques
Format: Document (PDF)

Title: HELIUM SPEECH PROCESSING BY LINEAR PREDICTION METHOD.
Creator: LEE, HYUN JICK., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The human speech production system is reviewed through general acoustic theory. Based upon that, the characteristics of helium speech is compared to normal speech. The Linear Prediction algorithm is derived for computer implementation by recursive formulas. The correction factors for the vocal tract area functions are found from simulated helium speech and normal speech data for four vowels. By the correction factors, new corrected area functions are applied to the Linear Prediction algorithm...
Show moreThe human speech production system is reviewed through general acoustic theory. Based upon that, the characteristics of helium speech is compared to normal speech. The Linear Prediction algorithm is derived for computer implementation by recursive formulas. The correction factors for the vocal tract area functions are found from simulated helium speech and normal speech data for four vowels. By the correction factors, new corrected area functions are applied to the Linear Prediction algorithm so that new synthesis filters can be built. The output of the algorithm is enhanced helium speech.
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Date Issued: 1985
PURL: http://purl.flvc.org/fcla/dt/14244
Subject Headings: Acoustical engineering, Underwater acoustics
Format: Document (PDF)

Title: Mismatch cancellation in quadrature bandpass delta-sigma modulators using an error shaping technique.
Creator: Riches, James John., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Techniques for shaping component mismatch error in the real and imaginary paths of a complex (quadrature) delta-sigma are studied, simulated and compared to existing techniques. Complex bandpass delta-sigma modulators provide improved performance over a pair of real bandpass delta-sigma modulators of the same order in the conversion of narrow-band quadrature IF (intermediate frequency) signals. This is possible due to elimination of redundant conjugate pairs of poles and zeros in its noise...
Show moreTechniques for shaping component mismatch error in the real and imaginary paths of a complex (quadrature) delta-sigma are studied, simulated and compared to existing techniques. Complex bandpass delta-sigma modulators provide improved performance over a pair of real bandpass delta-sigma modulators of the same order in the conversion of narrow-band quadrature IF (intermediate frequency) signals. This is possible due to elimination of redundant conjugate pairs of poles and zeros in its noise and signal transfer function. Mismatches in the modulators real and imaginary paths, however, results in spectral leakage of image band interference and image band quantization noise to the passband of the converted output. Strategic pole-zero placement, as well as adaptive techniques have been studied in earlier works. This thesis will take advantage of the inherent dual paths of the complex bandpass delta-sigma modulator to reduce component mismatch effects using a switched capacitor error shaping technique.
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Date Issued: 2000
PURL: http://purl.flvc.org/fcla/dt/15783
Subject Headings: Digital-to-analog converters, Modulators (Electronics), Electric filters, Bandpass
Format: Document (PDF)

Title: Multi-pulse excited linear prediction for synthesizing the guitar.
Creator: Leeds, David Scott., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In this paper we propose using parametric modeling by employing a Multi-Pulse Excited Linear Predictive Coded (MPE-LPC) filter to synthesize the guitar. First we introduce different methods for sound synthesis. A detailed discussion including the derivation of LPC and MPE presented. Then we study the impulse and steady state response of the guitar signal. An implementation of the MPE-LPC method to model the guitar is covered in detail and opportunities to improve the compression ratio are...
Show moreIn this paper we propose using parametric modeling by employing a Multi-Pulse Excited Linear Predictive Coded (MPE-LPC) filter to synthesize the guitar. First we introduce different methods for sound synthesis. A detailed discussion including the derivation of LPC and MPE presented. Then we study the impulse and steady state response of the guitar signal. An implementation of the MPE-LPC method to model the guitar is covered in detail and opportunities to improve the compression ratio are discussed. We then present simulation results with a set of fixed parameters, which are used as a benchmark to observe performance trade-offs by varying the model parameters to improve the compression ratio. Finally, we discuss limitations of the modeling algorithm for use with wide-band transient musical sounds and possible applications of the MPE-LPC model as a method to dynamically calculate samples for use with wavetable synthesis of steady state sounds.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/12759
Subject Headings: Computer music, Electric guitar, Signal processing--Digital techniques
Format: Document (PDF)

Title: Multiresolution analysis of glottal pulses.
Creator: Miguel, Agnieszka C., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Glottal pulse models provide vocal tract excitation signals which are used in producing high quality speech. Most of the currently used glottal pulse models are obtained by concatenating a small number of parametric functions over the pitch period. In this thesis, a new glottal pulse model is proposed. It is an alternative approach, which is based on the projection of glottal volume velocity over multiresolution subspaces spanned by wavelets and scaling functions. A detailed multiresolution...
Show moreGlottal pulse models provide vocal tract excitation signals which are used in producing high quality speech. Most of the currently used glottal pulse models are obtained by concatenating a small number of parametric functions over the pitch period. In this thesis, a new glottal pulse model is proposed. It is an alternative approach, which is based on the projection of glottal volume velocity over multiresolution subspaces spanned by wavelets and scaling functions. A detailed multiresolution analysis of the glottal models is performed using the compactly supported orthogonal Daubechies wavelets. The wavelet representation has been tested for optimality in terms of the reconstruction error and the energy compactness of the coefficients. It is demonstrated that by choosing proper parameters of the wavelet representation, high compression ratios and low rms error can be achieved.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/15334
Subject Headings: Signal processing, Speech processing systems, Wavelets (Mathematics)--Data processing
Format: Document (PDF)

Title: A novel face recognition transformational model and its inherent and optimal classification through a computationally efficient statistical algorithm.
Creator: Kyperountas, Marios C., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This thesis is concerned with the development of a new face recognition method that has a high recognition performance and is computationally efficient, so that it can be applied to real time processes. A background research is presented, summarizing the most dominant face recognition methods, with an emphasis to the most popular statistical method, the 'Eigenfaces'. Initially, a new algorithm is developed based only on the computational efficiency criterion. It is simulated, and criterions...
Show moreThis thesis is concerned with the development of a new face recognition method that has a high recognition performance and is computationally efficient, so that it can be applied to real time processes. A background research is presented, summarizing the most dominant face recognition methods, with an emphasis to the most popular statistical method, the 'Eigenfaces'. Initially, a new algorithm is developed based only on the computational efficiency criterion. It is simulated, and criterions for achieving higher recognition rates are experimentally and theoretically determined. A new space transform is introduced, which enhances the algorithm's recognition capabilities. Its optimum classification measure is mathematically proven to be one that is inherently provided by the new face recognition algorithm. Finally, the developed method is evaluated, and experimentally compared against the 'Eigenfaces' method, using face data.
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Date Issued: 2003
PURL: http://purl.flvc.org/fcla/dt/13034
Subject Headings: Human face recognition (Computer science), Eigenfunctions
Format: Document (PDF)

Title: Performance analysis of multitaper spectrum estimation.
Creator: Skoro Kaskarovska, Violeta, Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: We characterize the Multitaper Spectral Estimation method as a tool for stationary signal analysis. We compare its performance to the conventional periodogram, the parametric autoregressive and multitaper autoregressive spectral estimates. We analyze single and two frequency sinusoids with additive Gaussian white noise and autoregressive processes of orders 2, 4 and 24. We extend its application to non-stationary signals and develop the multitaper spectrogram. We test the spectrograms with...
Show moreWe characterize the Multitaper Spectral Estimation method as a tool for stationary signal analysis. We compare its performance to the conventional periodogram, the parametric autoregressive and multitaper autoregressive spectral estimates. We analyze single and two frequency sinusoids with additive Gaussian white noise and autoregressive processes of orders 2, 4 and 24. We extend its application to non-stationary signals and develop the multitaper spectrogram. We test the spectrograms with simulated non-stationary autoregressive process of order 2 as the magnitude of its poles vary between 0 and 1 and the angle of the poles vary between 0 and pi. Our results show that the multitaper spectral estimate can be parameterized and is more accurate than others tested for non-sinusoidal signals. We also show applications to aero-acoustic data analysis.
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Date Issued: 2005
PURL: http://purl.flvc.org/fcla/dt/13235
Subject Headings: Spectral theory (Mathematics), Signal processing--Mathematics, System identification, Power spectra
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.
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/15203
Subject Headings: Image compression--Digital techniques, Image processing--Digital techniques, Image transmission--Digital techniques, Coding theory, Vector fields
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 non-stationary 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.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/11965
Subject Headings: Eigenvalues, Eigenvectors, Wavelets (Mathematics)
Format: Document (PDF)

Title: Time-frequency 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 Wigner-Ville 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 discrete-time/continuous-frequency smoothing kernel. Although both time-variant and shift invariant versions of the estimator are developed, emphasis is placed on the shift-invariant version which is designed to estimate the WVS over an entire...
Show moreThis thesis provides detailed analysis and design techniques for Wigner-Ville 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 discrete-time/continuous-frequency smoothing kernel. Although both time-variant and shift invariant versions of the estimator are developed, emphasis is placed on the shift-invariant 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 quasi-stationary based estimators, both for the autocorrelation estimator and for the WVS estimator. The concept of quasi-stationarity is extended to cyclostationary models, and we develop a novel measure of kernel smoothing and variance reduction termed the time-bandwidth area. This is a generalization of time-bandwidth 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 quasi-stationary 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 Blackman-Tukey 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 trade-off between variance reduction and bias using conventional estimators. In the examples any assumption of quasi-stationarity 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.
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Date Issued: 1997
PURL: http://purl.flvc.org/fcla/dt/12537
Subject Headings: Signal processing, Wigner distribution
Format: Document (PDF)

Title: Voice activity detection over multiresolution subspaces.
Creator: Schultz, Robert Carl., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Society's increased demand for communications requires searching for techniques that preserve bandwidth. It has been observed that much of the time spent during telephone communications is actually idle time with no voice activity present. Detecting these idle periods and preventing transmission during these idle periods can aid in reducing bandwidth requirements during high traffic periods. While techniques exist to perform this detection, certain types of noise can prove difficult at best...
Show moreSociety's increased demand for communications requires searching for techniques that preserve bandwidth. It has been observed that much of the time spent during telephone communications is actually idle time with no voice activity present. Detecting these idle periods and preventing transmission during these idle periods can aid in reducing bandwidth requirements during high traffic periods. While techniques exist to perform this detection, certain types of noise can prove difficult at best for signal detection. The use of wavelets with multi-resolution subspaces can aid detection by providing noise whitening and signal matching. This thesis explores its use and proposes a technique for detection.
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Date Issued: 1999
PURL: http://purl.flvc.org/fcla/dt/15740
Subject Headings: Speech processing systems, Signal processing--Digital techniques, Wavelets (Mathematics)
Format: Document (PDF)

Title: Wavelet transform-based digital signal processing.
Creator: Basbug, Filiz., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This study deals with applying the wavelet transform to mainly two different areas of signal processing: adaptive signal processing, and signal detection. It starts with background information on the theory of wavelets with an emphasis on the multiresolution representation of signals by the wavelet transform in Chapter 1. Chapter 2 begins with an overview of adaptive filtering in general and extends it to transform domain adaptive filtering. Later in the chapter, a novel adaptive filtering...
Show moreThis study deals with applying the wavelet transform to mainly two different areas of signal processing: adaptive signal processing, and signal detection. It starts with background information on the theory of wavelets with an emphasis on the multiresolution representation of signals by the wavelet transform in Chapter 1. Chapter 2 begins with an overview of adaptive filtering in general and extends it to transform domain adaptive filtering. Later in the chapter, a novel adaptive filtering architecture using the wavelet transform is introduced. The performance of this new structure is evaluated by using the LMS algorithm with variations in step size. As a result of this study, the wavelet transform based adaptive filter is shown to reduce the eigenvalue ratio, or condition number, of the input signal. As a result, the new structure is shown to have faster convergence, implying an improvement in the ability to track rapidly changing signals. Chapter 3 deals with signal detection with the help of the wavelet transform. One scheme studies signal detection by projecting the input signal onto different scales. The relationship between this approach and that of matched filtering is established. Then the effect of different factors on signal detection with the wavelet transform is examined. It is found that the method is robust in the presence of white noise. Also, the wavelets are analyzed as eigenfunctions of a certain random process, and how this gives way to optimal receiver design is shown. It is further demonstrated that the design of an optimum receiver leads to the wavelet transform based adaptive filter structure described in Chapter 2.
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Date Issued: 1993
PURL: http://purl.flvc.org/fcla/dt/12354
Subject Headings: Wavelets (Mathematics), Signal processing--Digital techniques
Format: Document (PDF)

Title: A wavelet-based 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 non-white noise is investigated. We show empirical results that the wavelet transform provides an approximate Karhunen-Loeve expansion for 1/f-type noise. Since whitening can improve only broadband signals, a new method for synchronization signal design in wavelet subspaces with increased energy-to-peak 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.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/12778
Subject Headings: Wavelets (Mathematics), Underwater acoustics
Format: Document (PDF)

Signal processing--Digital techniques (5)	+ -
Wavelets (Mathematics) (4)	+ -
Signal processing (3)	+ -
Speech processing systems (3)	+ -
Underwater acoustics (2)	+ -

Acoustical engineering (1)	+ -
Coding theory (1)	+ -
Computer Science (1)	+ -
Computer music (1)	+ -
Decision support systems. (1)	+ -
Digital-to-analog converters (1)	+ -
Eigenfunctions (1)	+ -
Eigenvalues (1)	+ -
Eigenvectors (1)	+ -
Electric filters, Bandpass (1)	+ -
Electric guitar (1)	+ -
Electronic countermeasures (1)	+ -
Engineering, Electronics and Electrical (1)	+ -
Human face recognition (Computer science) (1)	+ -
Image compression--Digital techniques (1)	+ -
Image processing--Digital techniques (1)	+ -
Image transmission--Digital techniques (1)	+ -
Imaging systems in medicine. (1)	+ -
Medicine--Data processing. (1)	+ -
Modulators (Electronics) (1)	+ -
Pattern recognition systems. (1)	+ -
Phonocardiography. (1)	+ -
Power spectra (1)	+ -
Programming languages (Electronic computers) (1)	+ -
Signal processing--Mathematics (1)	+ -

Department of Computer and Electrical Engineering and Computer Science (17)	+ -
Florida Atlantic University (17)	+ -
Barrett, Raymond L. Jr. (1)	+ -
Basbug, Filiz. (1)	+ -
Frederick, Thomas James. (1)	+ -

Kyperountas, Marios C. (1)	+ -
Kyperountas, Spyros C. (1)	+ -
LEE, HYUN JICK. (1)	+ -
Leeds, David Scott. (1)	+ -
Lieber, Claude (1)	+ -
Lopez, Juan J. (1)	+ -
McLean, William Gregory. (1)	+ -
Miguel, Agnieszka C. (1)	+ -
Petljanski, Branko. (1)	+ -
Rajamani, Kannan. (1)	+ -
Riches, James John. (1)	+ -
Schultz, Robert Carl. (1)	+ -
Skoro Kaskarovska, Violeta (1)	+ -
WODKE, KENNETH E. (1)	+ -

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