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Description
Ultrasound imaging is one of the major medical imaging modalities. It is cheap, non-invasive and has low power consumption. Doppler processing is an important part of many ultrasound imaging systems. It is used to provide blood velocity information and is built on top of B-mode systems. We investigate the performance

Ultrasound imaging is one of the major medical imaging modalities. It is cheap, non-invasive and has low power consumption. Doppler processing is an important part of many ultrasound imaging systems. It is used to provide blood velocity information and is built on top of B-mode systems. We investigate the performance of two velocity estimation schemes used in Doppler processing systems, namely, directional velocity estimation (DVE) and conventional velocity estimation (CVE). We find that DVE provides better estimation performance and is the only functioning method when the beam to flow angle is large. Unfortunately, DVE is computationally expensive and also requires divisions and square root operations that are hard to implement. We propose two approximation techniques to replace these computations. The simulation results on cyst images show that the proposed approximations do not affect the estimation performance. We also study backend processing which includes envelope detection, log compression and scan conversion. Three different envelope detection methods are compared. Among them, FIR based Hilbert Transform is considered the best choice when phase information is not needed, while quadrature demodulation is a better choice if phase information is necessary. Bilinear and Gaussian interpolation are considered for scan conversion. Through simulations of a cyst image, we show that bilinear interpolation provides comparable contrast-to-noise ratio (CNR) performance with Gaussian interpolation and has lower computational complexity. Thus, bilinear interpolation is chosen for our system.
ContributorsWei, Siyuan (Author) / Chakrabarti, Chaitali (Thesis advisor) / Frakes, David (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2013
Description
Several contemporary clarinet works use Chinese folk music elements from different regions in new compositions to entice listener's and performer's appreciation of Chinese culture. However, to date, limited academic research on this topic exists. This research paper introduces six contemporary clarinet works by six Chinese composers: Qigang Chen's Morning Song,

Several contemporary clarinet works use Chinese folk music elements from different regions in new compositions to entice listener's and performer's appreciation of Chinese culture. However, to date, limited academic research on this topic exists. This research paper introduces six contemporary clarinet works by six Chinese composers: Qigang Chen's Morning Song, Yan Wang's Mu ma zhi ge (The Song of Grazing Horses), An-lun Huang's Capriccio for Clarinet and Strings Op. 41, Bijing Hu's The Sound of Pamir Clarinet Concerto, Mei-Mi Lan's Concerto for Clarinet and String Orchestra with Harp and Percussion, and Yu-Hui Chang's Three Fantasias for Solo Clarinet in B-flat. They are examined from different perspectives, including general structure, style, and rejuvenated folk music use. The focus of this research paper is to investigate the use of Chinese folk music in several works in collaboration with the composers. The author found that although contemporary composers use Chinese folk music differently in their works (i.e., some use melodies, others use harmony, while others use modes), each work celebrates the music and culture of the folk music on which the pieces are based. It is the author's hope to stimulate people's interest in music using Chinese folk music elements, and bring these lesser known works into the common clarinet repertoire.
ContributorsFeng, Chiao-Ting (Author) / Spring, Robert (Thesis advisor) / Gardner, Joshua (Committee member) / Micklich, Albie (Committee member) / Rogers, Rodney (Committee member) / Schuring, Martin (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Bright Summer, a one-movement piece for orchestra, was composed in Arizona, and completed in February 2013. The piece is approximately twelve minutes long. The motivation for writing this piece was the death of my mother the year before, in 2012. The prevailing mood of this work is bright and pleasant,

Bright Summer, a one-movement piece for orchestra, was composed in Arizona, and completed in February 2013. The piece is approximately twelve minutes long. The motivation for writing this piece was the death of my mother the year before, in 2012. The prevailing mood of this work is bright and pleasant, expressing my mother's cheerful personality when she was alive. It also portrays bright summer days which resemble my mother's spirit. Thus, soundscape plays an important role in this work. It depicts summer breeze, rustling sounds of leaves, and, to translate a Korean saying, "high blue skies." This soundscape opens the piece as well as closes it. In the middle section, the fast upbeat themes represent my mother's witty and optimistic personality. The piece also contains the presence of a hymn tune, The Love of God is Greater Far, which informs the motivic content and also functions as the climax of the piece. It was my mother's favorite hymn and we used to sing it together following her conversion to Christianity. The piece contains three main sections, which are held together by transitional material based on the soundscape and metric modulations. Unlike my earlier works, Bright Summer is tonal, with upper tertian harmonies prevailing throughout the piece. However, the opening and closing soundscapes do not have functional harmonies. For example, tertian chords appear and vanish silently, leaving behind some resonant sounds without any harmonic progression. Overall, the whole piece is reminiscent of my mother who lived a beautiful life.
ContributorsKim, JeeYeon (Composer) / DeMars, James (Thesis advisor) / Hackbarth, Glenn (Committee member) / Rogers, Rodney (Committee member) / Levy, Benjamin (Committee member) / Rockmaker, Jody (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Distributed inference has applications in a wide range of fields such as source localization, target detection, environment monitoring, and healthcare. In this dissertation, distributed inference schemes which use bounded transmit power are considered. The performance of the proposed schemes are studied for a variety of inference problems. In the first

Distributed inference has applications in a wide range of fields such as source localization, target detection, environment monitoring, and healthcare. In this dissertation, distributed inference schemes which use bounded transmit power are considered. The performance of the proposed schemes are studied for a variety of inference problems. In the first part of the dissertation, a distributed detection scheme where the sensors transmit with constant modulus signals over a Gaussian multiple access channel is considered. The deflection coefficient of the proposed scheme is shown to depend on the characteristic function of the sensing noise, and the error exponent for the system is derived using large deviation theory. Optimization of the deflection coefficient and error exponent are considered with respect to a transmission phase parameter for a variety of sensing noise distributions including impulsive ones. The proposed scheme is also favorably compared with existing amplify-and-forward (AF) and detect-and-forward (DF) schemes. The effect of fading is shown to be detrimental to the detection performance and simulations are provided to corroborate the analytical results. The second part of the dissertation studies a distributed inference scheme which uses bounded transmission functions over a Gaussian multiple access channel. The conditions on the transmission functions under which consistent estimation and reliable detection are possible is characterized. For the distributed estimation problem, an estimation scheme that uses bounded transmission functions is proved to be strongly consistent provided that the variance of the noise samples are bounded and that the transmission function is one-to-one. The proposed estimation scheme is compared with the amplify and forward technique and its robustness to impulsive sensing noise distributions is highlighted. It is also shown that bounded transmissions suffer from inconsistent estimates if the sensing noise variance goes to infinity. For the distributed detection problem, similar results are obtained by studying the deflection coefficient. Simulations corroborate our analytical results. In the third part of this dissertation, the problem of estimating the average of samples distributed at the nodes of a sensor network is considered. A distributed average consensus algorithm in which every sensor transmits with bounded peak power is proposed. In the presence of communication noise, it is shown that the nodes reach consensus asymptotically to a finite random variable whose expectation is the desired sample average of the initial observations with a variance that depends on the step size of the algorithm and the variance of the communication noise. The asymptotic performance is characterized by deriving the asymptotic covariance matrix using results from stochastic approximation theory. It is shown that using bounded transmissions results in slower convergence compared to the linear consensus algorithm based on the Laplacian heuristic. Simulations corroborate our analytical findings. Finally, a robust distributed average consensus algorithm in which every sensor performs a nonlinear processing at the receiver is proposed. It is shown that non-linearity at the receiver nodes makes the algorithm robust to a wide range of channel noise distributions including the impulsive ones. It is shown that the nodes reach consensus asymptotically and similar results are obtained as in the case of transmit non-linearity. Simulations corroborate our analytical findings and highlight the robustness of the proposed algorithm.
ContributorsDasarathan, Sivaraman (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Reisslein, Martin (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart

Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart of these algorithms is particle filtering (PF), a sequential Monte Carlo technique used to estimate the unknown parameters of dynamic systems. First, we analyze the bottlenecks in existing PF algorithms, and we propose a new parallel PF (PPF) algorithm based on the independent Metropolis-Hastings (IMH) algorithm. We show that the proposed PPF-IMH algorithm improves the root mean-squared error (RMSE) estimation performance, and we demonstrate that a parallel implementation of the algorithm results in significant reduction in inter-processor communication. We apply our implementation on a Xilinx Virtex-5 field programmable gate array (FPGA) platform to demonstrate that, for a one-dimensional problem, the PPF-IMH architecture with four processing elements and 1,000 particles can process input samples at 170 kHz by using less than 5% FPGA resources. We also apply the proposed PPF-IMH to waveform-agile sensing to achieve real-time tracking of dynamic targets with high RMSE tracking performance. We next integrate the PPF-IMH algorithm to track the dynamic parameters in neural sensing when the number of neural dipole sources is known. We analyze the computational complexity of a PF based method and propose the use of multiple particle filtering (MPF) to reduce the complexity. We demonstrate the improved performance of MPF using numerical simulations with both synthetic and real data. We also propose an FPGA implementation of the MPF algorithm and show that the implementation supports real-time tracking. For the more realistic scenario of automatically estimating an unknown number of time-varying neural dipole sources, we propose a new approach based on the probability hypothesis density filtering (PHDF) algorithm. The PHDF is implemented using particle filtering (PF-PHDF), and it is applied in a closed-loop to first estimate the number of dipole sources and then their corresponding amplitude, location and orientation parameters. We demonstrate the improved tracking performance of the proposed PF-PHDF algorithm and map it onto a Xilinx Virtex-5 FPGA platform to show its real-time implementation potential. Finally, we propose the use of sensor scheduling and compressive sensing techniques to reduce the number of active sensors, and thus overall power consumption, of electroencephalography (EEG) systems. We propose an efficient sensor scheduling algorithm which adaptively configures EEG sensors at each measurement time interval to reduce the number of sensors needed for accurate tracking. We combine the sensor scheduling method with PF-PHDF and implement the system on an FPGA platform to achieve real-time tracking. We also investigate the sparsity of EEG signals and integrate compressive sensing with PF to estimate neural activity. Simulation results show that both sensor scheduling and compressive sensing based methods achieve comparable tracking performance with significantly reduced number of sensors.
ContributorsMiao, Lifeng (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Thesis advisor) / Zhang, Junshan (Committee member) / Bliss, Daniel (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This research examines the current challenges of using Lamb wave interrogation methods to localize fatigue crack damage in a complex metallic structural component subjected to unknown temperatures. The goal of this work is to improve damage localization results for a structural component interrogated at an unknown temperature, by developing a

This research examines the current challenges of using Lamb wave interrogation methods to localize fatigue crack damage in a complex metallic structural component subjected to unknown temperatures. The goal of this work is to improve damage localization results for a structural component interrogated at an unknown temperature, by developing a probabilistic and reference-free framework for estimating Lamb wave velocities and the damage location. The methodology for damage localization at unknown temperatures includes the following key elements: i) a model that can describe the change in Lamb wave velocities with temperature; ii) the extension of an advanced time-frequency based signal processing technique for enhanced time-of-flight feature extraction from a dispersive signal; iii) the development of a Bayesian damage localization framework incorporating data association and sensor fusion. The technique requires no additional transducers to be installed on a structure, and allows for the estimation of both the temperature and the wave velocity in the component. Additionally, the framework of the algorithm allows it to function completely in an unsupervised manner by probabilistically accounting for all measurement origin uncertainty. The novel algorithm was experimentally validated using an aluminum lug joint with a growing fatigue crack. The lug joint was interrogated using piezoelectric transducers at multiple fatigue crack lengths, and at temperatures between 20°C and 80°C. The results showed that the algorithm could accurately predict the temperature and wave speed of the lug joint. The localization results for the fatigue damage were found to correlate well with the true locations at long crack lengths, but loss of accuracy was observed in localizing small cracks due to time-of-flight measurement errors. To validate the algorithm across a wider range of temperatures the electromechanically coupled LISA/SIM model was used to simulate the effects of temperatures. The numerical results showed that this approach would be capable of experimentally estimating the temperature and velocity in the lug joint for temperatures from -60°C to 150°C. The velocity estimation algorithm was found to significantly increase the accuracy of localization at temperatures above 120°C when error due to incorrect velocity selection begins to outweigh the error due to time-of-flight measurements.
ContributorsHensberry, Kevin (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2013
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Description
ABSTRACT Musicians endure injuries at an alarming rate, largely due to the misuse of their bodies. Musicians move their bodies for a living and therefore should understand how to move them in a healthy way. This paper presents Body Mapping as an injury prevention technique specifically directed toward collaborative pianists.

ABSTRACT Musicians endure injuries at an alarming rate, largely due to the misuse of their bodies. Musicians move their bodies for a living and therefore should understand how to move them in a healthy way. This paper presents Body Mapping as an injury prevention technique specifically directed toward collaborative pianists. A body map is the self-representation in one's brain that includes information on the structure, function, and size of one's body; Body Mapping is the process of refining one's body map to produce coordinated movement. In addition to preventing injury, Body Mapping provides a means to achieve greater musical artistry through the training of movement, attention, and the senses. With the main function of collaborating with one or more musical partners, a collaborative pianist will have the opportunity to share the knowledge of Body Mapping with many fellow musicians. This study demonstrates the author's credentials as a Body Mapping instructor, the current status of the field of collaborative piano, and the recommendation for increased body awareness. Information on the nature and abundance of injuries and Body Mapping concepts are also analyzed. The study culminates in a course syllabus entitled An Introduction to Collaborative Piano and Body Mapping with the objective of imparting fundamental collaborative piano skills integrated with proper body use. The author hopes to inform educators of the benefits of prioritizing health among their students and to provide a Body Mapping foundation upon which their students can build technique.
ContributorsBindel, Jennifer (Author) / Campbell, Andrew (Thesis advisor) / Doan, Jerry (Committee member) / Rogers, Rodney (Committee member) / Ryan, Russell (Committee member) / Schuring, Martin (Committee member) / Arizona State University (Publisher)
Created2013
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Description
There are a significant number of musical compositions for violin by composers who used folk songs and dances of various cultures in their music, including works by George Enescu, Béla Bartók and György Ligeti. Less known are pieces that draw on the plethora of melodies and rhythms from Turkey. The

There are a significant number of musical compositions for violin by composers who used folk songs and dances of various cultures in their music, including works by George Enescu, Béla Bartók and György Ligeti. Less known are pieces that draw on the plethora of melodies and rhythms from Turkey. The purpose of this paper is to help performers become more familiar with two such compositions: Fazil Say's Sonata for Violin and Piano and Cleopatra for Solo Violin. Fazil Say (b. 1970) is considered to be a significant, contemporary Turkish composer. Both of the works discussed in this document simulate traditional "Eastern" instruments, such as the kemenҫe, the baðlama, the kanun and the ud. Additionally, both pieces use themes from folk melodies of Turkey, Turkish dance rhythms and Arabian scales, all framed within traditional structural techniques, such as ostinato bass and the fughetta. Both the Sonata for Violin and Piano and Cleopatra are enormously expressive and musically interesting works, demanding virtuosity and a wide technical range. Although this document does not purport to be a full theoretical analysis, by providing biographical information, analytical descriptions, notes regarding interpretation, and suggestions to assist performers in overcoming technical obstacles, the writer hopes to inspire other violinists to consider learning and performing these works.
ContributorsKalantzi, Panagiota (Author) / Jiang, Danwen (Thesis advisor) / Hill, Gary (Committee member) / Rogers, Rodney (Committee member) / Rotaru, Catalin (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The purpose of this project is twofold: to contribute to the literature of chamber ensembles comprising mixed wind, string, and percussion instruments by producing arrangements of three piano rags by William Bolcom; and to highlight Bolcom's pivotal role in the ragtime revival of the 1960's and 1970's. Through his influence

The purpose of this project is twofold: to contribute to the literature of chamber ensembles comprising mixed wind, string, and percussion instruments by producing arrangements of three piano rags by William Bolcom; and to highlight Bolcom's pivotal role in the ragtime revival of the 1960's and 1970's. Through his influence as a scholar, composer, and performer, Bolcom (b. 1938), one of the most prominent American composers of his generation, helped garner respect for ragtime as art music and as one of America's great popular music genres. Bolcom's 3 Ghost Rags were written in the tradition of classic piano rags, but with a compositional sensibility that is influenced by the fifty years that separate them from the close of the original ragtime era. The basis for the present orchestrations of 3 Ghost Rags is the collection of instrumental arrangements of piano rags published by Stark Publishing Co., entitled Standard High-Class Rags. More familiarly known as the "Red Back Book," this publication was representative of the exchange of repertoire between piano and ensembles and served as a repertory for the various ragtime revivals that occurred later in the twentieth century. In creating these orchestrations of Bolcom's piano rags, the author strove to provide another medium in which Bolcom's music could be performed, while orchestrating the music for an historically appropriate ensemble.
ContributorsMelley, Eric Charles (Author) / Hill, Gary W. (Thesis advisor) / Bailey, Wayne (Committee member) / Norton, Kay (Committee member) / Rogers, Rodney (Committee member) / Russell, Timothy (Committee member) / Arizona State University (Publisher)
Created2013
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Description
A signal with time-varying frequency content can often be expressed more clearly using a time-frequency representation (TFR), which maps the signal into a two-dimensional function of time and frequency, similar to musical notation. The thesis reviews one of the most commonly used TFRs, the Wigner distribution (WD), and discusses its

A signal with time-varying frequency content can often be expressed more clearly using a time-frequency representation (TFR), which maps the signal into a two-dimensional function of time and frequency, similar to musical notation. The thesis reviews one of the most commonly used TFRs, the Wigner distribution (WD), and discusses its application in Fourier optics: it is shown that the WD is analogous to the spectral dispersion that results from a diffraction grating, and time and frequency are similarly analogous to a one dimensional spatial coordinate and wavenumber. The grating is compared with a simple polychromator, which is a bank of optical filters. Another well-known TFR is the short time Fourier transform (STFT). Its discrete version can be shown to be equivalent to a filter bank, an array of bandpass filters that enable localized processing of the analysis signals in different sub-bands. This work proposes a signal-adaptive method of generating TFRs. In order to minimize distortion in analyzing a signal, the method modifies the filter bank to consist of non-overlapping rectangular bandpass filters generated using the Butterworth filter design process. The information contained in the resulting TFR can be used to reconstruct the signal, and perfect reconstruction techniques involving quadrature mirror filter banks are compared with a simple Fourier synthesis sum. The optimal filter parameters of the rectangular filters are selected adaptively by minimizing the mean-squared error (MSE) from a pseudo-reconstructed version of the analysis signal. The reconstruction MSE is proposed as an error metric for characterizing TFRs; a practical measure of the error requires normalization and cross correlation with the analysis signal. Simulations were performed to demonstrate the the effectiveness of the new adaptive TFR and its relation to swept-tuned spectrum analyzers.
ContributorsWeber, Peter C. (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2012