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Title: Sparse representation classification of dolphin whistles using local binary patterns.
Creator: Esfahanian, Mahdi, Zhuang, Hanqi, Erdol, Nurgun, Graduate College
Date Issued: 2013-04-12
PURL: http://purl.flvc.org/fcla/dt/3361295
Subject Headings: Dolphins, Dolphin sounds, Bioacoustics
Format: Document (PDF)

Title: Sparse Representation Classification of Dolphin Whistles Using Gabor Wavelets.
Creator: Esfahanian, Mahdi, Zhuang, Hanqi, Graduate College, Erdol, Nurgun
Abstract/Description: This research presents a novel approach to categorize dolphin whistles into various types. Most accurate methods to identify dolphin whistles are tedious and not robust, especially in the presence of ocean noise. One of the biggest challenges of dolphin whistle extraction is the coexistence of short-time duration wide-band echo clicks with the whistles. In this research, a subspace of select orientation parameters of the 2D Gabor wavelet frames is utilized to enhance or suppress signals by...
Show moreThis research presents a novel approach to categorize dolphin whistles into various types. Most accurate methods to identify dolphin whistles are tedious and not robust, especially in the presence of ocean noise. One of the biggest challenges of dolphin whistle extraction is the coexistence of short-time duration wide-band echo clicks with the whistles. In this research, a subspace of select orientation parameters of the 2D Gabor wavelet frames is utilized to enhance or suppress signals by their orientation. The result is a Gabor image that contains a noise free grayscale representation of the fundamental dolphin whistle which is resampled and fed into the Sparse Representation Classifier. The classifier uses the l1 norm to select a match. Experimental studies conducted demonstrate: a a robust technique based on the Gabor wavelet filters in extracting reliable call patterns, and b the superior performance of Sparse Representation Classifier for identifying dolphin whistles by their call type.
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Date Issued: 2014
PURL: http://purl.flvc.org/fau/fd/FA00005146
Format: Document (PDF)

Title: DIGITAL IMAGE PROCESSING APPLIED TO CHARACTER RECOGNITION.
Creator: BEGUN, RALPH MURRAY., Florida Atlantic University, Erdol, Nurgun
Abstract/Description: Surveys are made of both character recognition and image processing. The need to apply image processing techniques to character recognition is pointed out. The fields are then combined and tested in sample programs. Simulations are made of recognition systems with and without image preprocessing. Processing techniques applied utilize Walsh-Hadamard transforms and l ocal window operators. Results indicate that image prepro c ess i ng improves recognition rates when noise degrades input images....
Show moreSurveys are made of both character recognition and image processing. The need to apply image processing techniques to character recognition is pointed out. The fields are then combined and tested in sample programs. Simulations are made of recognition systems with and without image preprocessing. Processing techniques applied utilize Walsh-Hadamard transforms and l ocal window operators. Results indicate that image prepro c ess i ng improves recognition rates when noise degrades input images. A system architecture is proposed for a hardware based video speed image processor operating on local image windows. The possible implementation of this processor is outlined.
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Date Issued: 1982
PURL: http://purl.flvc.org/fcla/dt/14120
Subject Headings: Image processing--Digital techniques, Optical character recognition devices, Pattern recognition systems
Format: Document (PDF)

Title: Implementation and representation of the discrete wavelet transform.
Creator: Efthymoglou, George P., Florida Atlantic University, Erdol, Nurgun
Abstract/Description: This thesis presents a comprehensive analysis of a relatively new transform for discrete time signals, called the Discrete Wavelet Transform (DWT). We find how this transform is connected with the already existing theory of perfect reconstruction filter banks and the recently introduced theory of multiresolution analysis. We use the conditions obtained from these two theories in order to understand the construction of wavelet filters, which also generate continuous functions that prove to...
Show moreThis thesis presents a comprehensive analysis of a relatively new transform for discrete time signals, called the Discrete Wavelet Transform (DWT). We find how this transform is connected with the already existing theory of perfect reconstruction filter banks and the recently introduced theory of multiresolution analysis. We use the conditions obtained from these two theories in order to understand the construction of wavelet filters, which also generate continuous functions that prove to constitute an orthonormal basis for the L$\sp2$ space. We also investigate the connection of this transform to the sampled wavelet series of nonorthogonal functions with good time-frequency localization properties. Finally, we see the way that the DWT maps a discrete signal in the phase plane and the applications that such representations incorporate.
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Date Issued: 1993
PURL: http://purl.flvc.org/fcla/dt/14944
Subject Headings: Wavelets (Mathematics), Integrals, Singular, Signal processing--Digital techniques
Format: Document (PDF)

Title: Non-separable two dimensional wavelets and their filter banks in polar coordinates.
Creator: Andric, Oleg., Florida Atlantic University, Erdol, Nurgun
Abstract/Description: The problems encountered in development and implementation of orthonormal two dimensional wavelet bases and their filter banks in polar coordinates are addressed. These wavelets and filter banks have possible applications in processing signals that are collected by sensors working in the polar coordinate system, such as biomedical and radar generated signals. The relationship between the space of measurable, square-integrable functions on the punctured polar coordinate system L^2(P) and space...
Show moreThe problems encountered in development and implementation of orthonormal two dimensional wavelet bases and their filter banks in polar coordinates are addressed. These wavelets and filter banks have possible applications in processing signals that are collected by sensors working in the polar coordinate system, such as biomedical and radar generated signals. The relationship between the space of measurable, square-integrable functions on the punctured polar coordinate system L^2(P) and space of measurable, square-integrable functions on the rectangular plane L^2(R^2) is developed. This allows us to develop complete wavelet bases in a more convenient and familiar surrounding of L^2(R^2) and to transport this theory to L^2(P). Corresponding filter banks are also developed. The implementation of wavelet analysis of punctured polar plane is discussed. An example of wavelet bases, filter banks, and implementation is provided.
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/15190
Subject Headings: Wavelets (Mathematics), Coordinates, Polar, Signal processing--Mathematical models
Format: Document (PDF)

Title: Frequency Line Tracking in Spectrograms Using Hidden Markov Models.
Creator: Gunes, Tuncay, Erdol, Nurgun, Florida Atlantic University
Abstract/Description: One of the limiting factors restricting aircraft landings at maJor airports is the minimum spacing requirements due to vortex wake avoidance. If it can be shown that the separation requirements are too conservative, then it may be possible to increase the rate of landings on a given runway. During August/September 2003, NASA and the (United States Department of Transportation) USDOT sponsored a wake acoustics test at the Denver International Airport. The central instrument of the test was a...
Show moreOne of the limiting factors restricting aircraft landings at maJor airports is the minimum spacing requirements due to vortex wake avoidance. If it can be shown that the separation requirements are too conservative, then it may be possible to increase the rate of landings on a given runway. During August/September 2003, NASA and the (United States Department of Transportation) USDOT sponsored a wake acoustics test at the Denver International Airport. The central instrument of the test was a large microphone phased array. Different types of aircrafts were recorded during landing and the acoustic data obtained was stored. From acoustic data the spectrograms were generated using the technique of AutoRegressive (AR) spectral estimation from multitaper autocorrelation estimates. Several sources of sound that are recorded in the audio files can be observed in the spectrograms. Some these signals, such as the noise generated from the aircraft engine can be identified easily because of their strength and the Doppler shift they undergo. In contrast to this, the wake vortex signal is weaker and does not exhibit a Doppler shift because it's stationary in space. Therefore it may not be identified easily because of the existence of stronger signals. The motive in our research is to develop methods to determine these strong signals that appear as spectral lines in the spectrogram. In the future, the results obtained in this work can be used to eliminate these strong signals from the spectrogram thus allowing us to see and identify wake vortex signal which is more important to us.
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Date Issued: 2006
PURL: http://purl.flvc.org/fau/fd/FA00012525
Subject Headings: Markov processes, Economics--Mathematical models, Wave structure function--Analysis, Adaptive control systems, Spectrum analysis
Format: Document (PDF)

Title: Interactive graphical tools for digital signal processing education.
Creator: Aksaray, Ali Ercument., Florida Atlantic University, Erdol, Nurgun
Abstract/Description: In this thesis, we develop a set of programs in the MATLAB RTM Graphical User Interface environment, for use as an Interactive Digital Signal Processing Laboratory. The software toolbox consists of programs on selected topics covered in undergraduate Digital Signal Processing courses. Care is taken to give the user sufficient degrees of freedom to illustrate the effect of various parameter changes. Program code is left open and well documented to allow expansion.
Date Issued: 2002
PURL: http://purl.flvc.org/fcla/dt/12960
Subject Headings: Signal processing--Digital techniques--Study and teaching, Multimedia systems, Graphical user interfaces (Computer systems)
Format: Document (PDF)

Title: Missing speech packet reconstruction based on the short-time energy and the zero-crossings.
Creator: Castelluccia, Claude., Florida Atlantic University, Erdol, Nurgun
Abstract/Description: A waveform substitution technique using interpolation based on such slow varying parameters of speech as short-time energy and average zero-crossing rate is developed for a packetized speech communication system. The system uses 64 Kbps conventional PCM for encoding and takes advantage of active talkpurts and silence intervals to increase the utilization efficiency of a digital link. The short-time energy and average zero-crossing rates calculated for the purpose of determining talkpurts are...
Show moreA waveform substitution technique using interpolation based on such slow varying parameters of speech as short-time energy and average zero-crossing rate is developed for a packetized speech communication system. The system uses 64 Kbps conventional PCM for encoding and takes advantage of active talkpurts and silence intervals to increase the utilization efficiency of a digital link. The short-time energy and average zero-crossing rates calculated for the purpose of determining talkpurts are transmitted in a preceeding packet. Hence, when a packet is pronounced "lost", its envelope and frequency characteristics are obtained from the previous packet and used to synthetize a substitution waveform which is free of annoying sounds that are due to abrupt changes in amplitude. Informal listening tests show that tolerable packet loss rate up to 40% are achievable with these procedures.
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Date Issued: 1991
PURL: http://purl.flvc.org/fcla/dt/14704
Subject Headings: Packet switching (Data transmission), Speech processing systems
Format: Document (PDF)

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: MACHINE LEARNING DEMODULATOR ARCHITECTURES FOR POWER-LIMITED COMMUNICATIONS.
Creator: Gorday, Paul E., Nurgun, Erdol, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
Abstract/Description: The success of deep learning has renewed interest in applying neural networks and other machine learning techniques to most fields of data and signal processing, including communications. Advances in architecture and training lead us to consider new modem architectures that allow flexibility in design, continued learning in the field, and improved waveform coding. This dissertation examines neural network architectures and training methods suitable for demodulation in power-limited...
Show moreThe success of deep learning has renewed interest in applying neural networks and other machine learning techniques to most fields of data and signal processing, including communications. Advances in architecture and training lead us to consider new modem architectures that allow flexibility in design, continued learning in the field, and improved waveform coding. This dissertation examines neural network architectures and training methods suitable for demodulation in power-limited communication systems, such as those found in wireless sensor networks. Such networks will provide greater connection to the world around us and are expected to contain orders of magnitude more devices than cellular networks. A number of standard and proprietary protocols span this space, with modulations such as frequency-shift-keying (FSK), Gaussian FSK (GFSK), minimum shift keying (MSK), on-off-keying (OOK), and M-ary orthogonal modulation (M-orth). These modulations enable low-cost radio hardware with efficient nonlinear amplification in the transmitter and noncoherent demodulation in the receiver.
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Date Issued: 2020
PURL: http://purl.flvc.org/fau/fd/FA00013511
Subject Headings: Deep learning, Machine learning--Technique, Demodulators, Wireless sensor networks, Computer network architectures
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: 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: 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: 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: 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: 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: 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: 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: 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: 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)

FAU Theses and Dissertations (24)	+ -
FAU Graduate Student Research (2)	+ -

Signal processing--Digital techniques (6)	+ -
Wavelets (Mathematics) (6)	+ -
Speech processing systems (4)	+ -
Signal processing (3)	+ -
Image processing--Digital techniques (2)	+ -

Underwater acoustics (2)	+ -
Acoustical engineering (1)	+ -
Adaptive control systems (1)	+ -
Bioacoustics (1)	+ -
Coding theory (1)	+ -
Computer Science (1)	+ -
Computer music (1)	+ -
Computer network architectures (1)	+ -
Coordinates, Polar (1)	+ -
Decision support systems. (1)	+ -
Deep learning (1)	+ -
Demodulators (1)	+ -
Digital-to-analog converters (1)	+ -
Dolphin sounds (1)	+ -
Dolphins (1)	+ -
Economics--Mathematical models (1)	+ -
Eigenfunctions (1)	+ -
Eigenvalues (1)	+ -
Eigenvectors (1)	+ -
Electric filters, Bandpass (1)	+ -
Electric guitar (1)	+ -
Electronic countermeasures (1)	+ -
Engineering, Electronics and Electrical (1)	+ -
Graphical user interfaces (Computer systems) (1)	+ -
Human face recognition (Computer science) (1)	+ -

Electronic Thesis or Dissertation (24)	+ -
abstract (1)	+ -
poster (1)	+ -

Erdol, Nurgun (25)	+ -
Florida Atlantic University (24)	+ -
College of Engineering and Computer Science (18)	+ -
Department of Computer and Electrical Engineering and Computer Science (18)	+ -
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