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Discrete signal representation using triangular basis functions
Title
Discrete signal representation using triangular basis functions.
Creator
Nallur, Padmanabha., Florida Atlantic University, Hartt, William H., College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
This thesis deals with the representation of discrete signals using triangular basis functions. Signals are usually represented by Fourier series expansions where the basis functions are cosine and sine functions which are all mutually orthogonal. The triangular basis functions used here are called TRIC (triangular cosine) and TRIS (triangular sine) functions. The TRIC and TRIS functions are like their cosine and sine function counterparts except that they are linear. The TRIC and TRIS...
Show moreThis thesis deals with the representation of discrete signals using triangular basis functions. Signals are usually represented by Fourier series expansions where the basis functions are cosine and sine functions which are all mutually orthogonal. The triangular basis functions used here are called TRIC (triangular cosine) and TRIS (triangular sine) functions. The TRIC and TRIS functions are like their cosine and sine function counterparts except that they are linear. The TRIC and TRIS functions are not all mutually orthogonal, though most of them are. A matrix method of representing discrete signals using TRIC and TRIS functions is presented. A discrete triangular transform matrix is developed and a method of deriving this matrix is presented. A Fortran program is written to derive the discrete triangular transform matrix and to prove the reconstruction of several basic functions like impulse, step, pulse and sinusoidal waveforms.
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Date Issued
1988
PURL
http://purl.flvc.org/fcla/dt/14451
Subject Headings
Signal processing--Mathematical models
Format
Document (PDF)
Non-separable two dimensional wavelets and their filter banks in polar coordinates
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)
Performance analysis of multitaper spectrum estimation
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)
Detection and classification of marine mammal sounds
Title
Detection and classification of marine mammal sounds.
Creator
Esfahanian, Mahdi, Zhuang, Hanqi, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
Ocean is home to a large population of marine mammals such as dolphins and whales and concerns over anthropogenic activities in the regions close to their habitants have been increased. Therefore the ability to detect the presence of these species in the field, to analyze and classify their vocalization patterns for signs of distress and distortion of their communication calls will prove to be invaluable in protecting these species. The objective of this research is to investigate methods...
Show moreOcean is home to a large population of marine mammals such as dolphins and whales and concerns over anthropogenic activities in the regions close to their habitants have been increased. Therefore the ability to detect the presence of these species in the field, to analyze and classify their vocalization patterns for signs of distress and distortion of their communication calls will prove to be invaluable in protecting these species. The objective of this research is to investigate methods that automatically detect and classify vocalization patterns of marine mammals. The first work performed is the classification of bottlenose dolphin calls by type. The extraction of salient and distinguishing features from recordings is a major part of this endeavor. To this end, two strategies are evaluated with real datasets provided by Woods Hole Oceanographic Institution: The first strategy is to use contour-based features such as Time-Frequency Parameters and Fourier Descriptors and the second is to employ texture-based features such as Local Binary Patterns (LBP) and Gabor Wavelets. Once dolphin whistle features are extracted for spectrograms, selection of classification procedures is crucial to the success of the process. For this purpose, the performances of classifiers such as K-Nearest Neighbor, Support Vector Machine, and Sparse Representation Classifier (SRC) are assessed thoroughly, together with those of the underlined feature extractors.
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Date Issued
2014
PURL
http://purl.flvc.org/fau/fd/FA00004282, http://purl.flvc.org/fau/fd/FA00004282
Subject Headings
Acoustic phenomena in nature, Marine mammals -- Effect of noise on, Marine mammals -- Vocalization, Signal processing -- Mathematics, Underwater acoustics, Wavelets (Mathematics)
Format
Document (PDF)