Browsing by Subject "Spectral analysis"
Now showing 1 - 5 of 5
Results Per Page
Sort Options
Item Acoustical analysis of choral voice matching and placement as it relates to group blend and tone(Texas Tech University, 2006-05) Basinger, Lynn; Killian, Janice; Bilkey, Andrea; Marks, Jonathan; Elrod, Pamela; Fischer, PeterThe purpose of this study is to exam the feasibility of using acoustical voice analysis techniques as research tools in the investigation of voice matching as it relates to choral blend and tone. Spectral analysis has been applied extensively to the study of the solo singing voice, but few studies have used these technologies in the study of groups of singers in a choral setting. Five female volunteers from the top auditioned choir at a major southwestern university were recorded singing the first phrase of "My Country 'Tis of Thee" individually. These singers (n=5) were then recorded in a variety of groupings of two, three and four singers based on Weston Noble’s voice matching techniques (Noble, 2005). Recordings from a live voice matching session of the entire women's section of this choir conducted by their regular director were also included in the master data set, thus allowing comparison of controlled voice matching and in-situ voice matching recordings. Following procedures established by Killian & Basinger, a panel of five experts was asked to respond via a 7 point Likert scale as to their judgment of the quality of choral blend to a random sampling of 50 examples from the master data set. The experts were professional choral conductors and graduate choral music educations majors. Their responses were used to rank the samples as to quality of blend. Subsequently, all samples were analyzed using several readily available, low-cost spectral analysis software programs. Data available from each program is compared and evaluated for its relevance. The user-friendliness, strengths, and weaknesses of each program are also addressed. Data include spectral analysis graphic displays, formant analysis, power vs. frequency plots, vowel matching comparisons, and pitch plots. Results of spectral analysis of each ranked sample are compared and potential indicators of choral blend are identified. An important outcome of this exploratory research are suggestions for further study and practical application of spectral analysis as a tool to further understanding in the field of choral blend and tone.Item Acoustical analysis of choral voice matching and placement as it relates to group blend and tone(2006-05) Basinger, Lynn; Killian, Janice; Elrod, Pamela; Marks, Jonathan; Fischer, Peter; Bilkey, AndreaThe purpose of this study is to exam the feasibility of using acoustical voice analysis techniques as research tools in the investigation of voice matching as it relates to choral blend and tone. Spectral analysis has been applied extensively to the study of the solo singing voice, but few studies have used these technologies in the study of groups of singers in a choral setting. Five female volunteers from the top auditioned choir at a major southwestern university were recorded singing the first phrase of "My Country 'Tis of Thee" individually. These singers (n=5) were then recorded in a variety of groupings of two, three and four singers based on Weston Noble’s voice matching techniques (Noble, 2005). Recordings from a live voice matching session of the entire women's section of this choir conducted by their regular director were also included in the master data set, thus allowing comparison of controlled voice matching and in-situ voice matching recordings. Following procedures established by Killian & Basinger, a panel of five experts was asked to respond via a 7 point Likert scale as to their judgment of the quality of choral blend to a random sampling of 50 examples from the master data set. The experts were professional choral conductors and graduate choral music educations majors. Their responses were used to rank the samples as to quality of blend. Subsequently, all samples were analyzed using several readily available, low-cost spectral analysis software programs. Data available from each program is compared and evaluated for its relevance. The user-friendliness, strengths, and weaknesses of each program are also addressed. Data include spectral analysis graphic displays, formant analysis, power vs. frequency plots, vowel matching comparisons, and pitch plots. Results of spectral analysis of each ranked sample are compared and potential indicators of choral blend are identified. An important outcome of this exploratory research are suggestions for further study and practical application of spectral analysis as a tool to further understanding in the field of choral blend and tone.Item Asymptotic and spectral analysis of nonselfadjoint operators generated by a coupled Euler-Bernoulli/Timoshenko beam model(Texas Tech University, 2002-05) Peterson, Cheryl AnneThis dissertation is devoted to the asymptotic and spectral analysis of a coupled Euler-Bernoulli and Timoshenko beam model. The model is governed by a system of two coupled differential equations and a two parameter family of boundary conditions modeling the action of self-straining actuators. The aforementioned equations of motion together with a two-parameter family of boundary conditions form a coupled linear hyperbolic system, which is equivalent to a single operator evolution equation in the energy space. That equation defines a semigroup of bounded operators. The dynamics generator of the semigroup is our main object of interest in the dissertation. For each set of boundary parameters, the dynamics generator has a compact inverse. If both boundary parameters are not purely imaginary numbers, then the dynamics generator is a nonselfadjoint operator in the energy space. We calculate the spectral asymptotics of the dynamics generator. We find that the spectrum lies in a strip parallel to the horizontal axis, and is asymptotically close to the horizontal axis, thus the system is stable, but is not uniformly stable. The latter fact has been observed in numerical simulations and in the present dissertation, it has been rigorously proven.Item Computational analysis of meditation(2011-08) Saggar, Manish; Miikkulainen, Risto; Saron, Clifford D.; Schnyer, David M.; Ballard, Dana H.; Ravikumar, PradeepMeditation training has been shown to improve attention and emotion regulation. However, the mechanisms responsible for these effects are largely unknown. In order to make further progress, a rigorous interdisciplinary approach that combines both empirical and theoretical experiments is required. This dissertation uses such an approach to analyze electroencephalogram (EEG) data collected during two three-month long intensive meditation retreats in four steps. First, novel tools were developed for preprocessing the EEG data. These tools helped remove ocular artifacts, muscular artifacts, and interference from power lines in a semi-automatic fashion. Second, in order to identify the cortical correlates of meditation, longitudinal changes in the cortical activity were measured using spectral analysis. Three main longitudinal changes were observed in the retreat participants: (1) reduced individual alpha frequency after training, similar reduction has been consistently found in experienced meditators; (2) reduced alpha-band power in the midline frontal region, which correlated with improved vigilance performance; and (3) reduced beta-band power in the parietal-occipital regions, which correlated with daily time spent in meditation and enhanced self-reported psychological well-being. Third, a formal computational model was developed to provide a concrete and testable theory about the underlying mechanisms. Four theoretical experiments were run, which showed, (1) reduced intrathalamic gain after training, suggesting enhanced alertness; (2) increased cortico-thalamic delay, which strongly correlated with the reduction in individual alpha frequency (found during spectral analysis); (3) reduction in intrathalamic gain provided increased stability to the brain; and (4) anterior-posterior division in the modeled reticular nucleus of the thalamus (TRN) layer and increased connectivity in the posterior region of TRN after training. Fourth, correlation analysis was performed to ground the changes in cortical activity and model parameters into changes in behavior and self-reported psychological functions. Through these four steps, a concrete theory of the mechanisms underlying focused-attention meditation was constructed. This theory provides both mechanistic and teleological reasoning behind the changes observed during meditation training. The theory further leads to several predictions, including the possibility that customized meditation techniques can be used to treat patients suffering from neurodevelopmental disorders and epilepsy. Lastly, the dissertation attempts to link the theory to the long-held views that meditation improves awareness, attention, stability, and psychological well-being.Item Nitrogen nutrition estimation of cotton using greenness and ground cover(2012-08) Muharam, Melissa; Maas, Stephan J.; Ritchie, Glen L.; Delahunty, Tina; Hequet, Eric F.; Leverington, DavidConventionally, plant N status is obtained destructively using tissue leaf N or petiole sap nitrate readings. In recent years, spectral analysis methods, including the chlorophyll meter technique, have gained popularity as an alternative to the conventional technique for estimating plant chlorophyll or N content. In cotton-related research, many previous studies have adopted correlation analysis to determine the best wavelengths for the aforementioned analysis. However, the specific wavelengths that were selected through this approach often differed from one location to another. Likewise, these specific wavelengths were variable at different scales of measurement, times of data acquisition and parameters of interest (i.e., N or chlorophyll). In this study, I propose a new method to estimate chlorophyll or N content based on the physical characteristics of cotton plants as affected by N fertilization. This study is described in three different chapters. In the first chapter, the response of growth parameters (plant height, plant width and percent ground cover) in manifesting differences caused by N fertilizations were investigated. I also examined the relationship between the cotton growth parameters and indicators of N status (leaf tissue N, petiole sap nitrate and chlorophyll meter readings). The main goal is to identify a growth parameter that could be used to complement spectral measurement as a method for estimating plant N status. The responses of the growth parameters were subject to the presence of other growth limiting factors besides N fertilization. Under water stress, plants might fail to display the effects of N treatments. Percent ground cover was found to be the growth parameter best affected by N fertilization. In general, this parameter showed significant effects of N treatments more readily than plant height or plant width. In addition, percent ground cover was better correlated with plant N indicators than the other two growth parameters. These results suggested that percent ground cover could be used along with spectral information acquired from plants for the purpose of estimating different levels of chlorophyll or N content. The strong relationship between percent ground cover and leaf tissue N or chlorophyll meter readings also suggested that it could be used to estimate plant N status when other growth factors were not limited. Leaf tissue N and chlorophyll meter readings were strongly and significantly correlated with growth parameters, especially ground cover. However, none of the growth parameters was significantly correlated with petiole sap nitrate, suggesting its limitation for estimating them. In the second chapter, I examined and compared the reflectance of cotton plants measured at three different spatial scales as related to N treatment effects. The importance of this examination was to select the best spatial scale(s) for estimating chlorophyll or N content. The three spatial scales were the individual leaf, the canopy, and the scene. At the leaf scale, N treatment effects were most apparent at 550 nm and 700 nm. N treatments did not significantly affect the internal leaf structure, and hence the NIR reflectance. Wavelengths sensitive to the N fertilization shifted to 600 nm and 700 nm when the measurements were made at the canopy level. NIR reflectance began to increase with increased N fertilization, as N treatments promoted biomass production and, thus, multiple scattering by the leaves. High LAI had the potential to affect the N treatment signals although its effects were not observed to be great in the data. At the leaf and canopy scales, reflectance measured in the visible region was a function of chlorophyll concentration. On the other hand, measurements made at the canopy scale in the NIR showed the effects of increasing biomass production. At the scene level, the effects of N treatments were most sensitive at wavelengths from 685 nm to 690 nm. NIR reflectance also increased with the amount of N applied. Only measurements made at the scene scale showed a consistent relationship between the amount of N fertilization and reflectance in both the visible and NIR regions. Notably, the primary contribution to this sensitivity was differences in percent ground cover as a result of N fertilization, rather than chlorophyll concentration. Large differences in percent ground cover had a strong influence on the N signals, where it could completely confound the N treatment effects. In comparison, LAI had minimal effects on N signals. Since N fertilization primarily affects cotton chlorophyll content and percent ground cover, selecting only one scale may not be sufficient to show the effects of N treatments. Therefore, combining spatial scales that are most responsive to chlorophyll content (either the leaf or canopy level) with the scale that best explains the variation in percent ground cover (the scene level) might be a practical approach for estimating the chlorophyll or N content of crops such as cotton. Additionally, results derived from this study concerning the inconsistency of spectral reflectance as related to the amount of N fertilization might explain previously unsuccessful attempts to directly transform measurements made at one scale to another. This study also emphasized the significance of accounting for the field of view of a sensor, since spectral signature properties changed significantly with the changing spatial scales. The last chapter describes and tests a novel method of combining measurements made at different spatial scales as an approach to estimate in-season chlorophyll or leaf N content of field-grown cotton. In this study, leaf greenness estimated from spectral measurements made at the individual leaf, canopy and scene levels was combined with percent ground cover to produce three different indices, named TCCLeaf, TCCCanopy, and TCCScene. These indices worked best for estimating leaf tissue N, but did not work well for estimating chlorophyll content. Use of these indices was most effective at early flowering. Prior to this growth stage, the utilization of these indices was not recommended. Of the three indices, TCCLeaf showed the best ability to estimate leaf tissue N at early flowering (r2 = 0.89). These results suggest that the use of green and red-edge wavelengths derived at the leaf scale is best for estimating leaf greenness. TCCCanopy had a slightly lower r2 value than TCCLeaf (0.76), suggesting that the utilization of yellow and red-edge wavelengths obtained at the canopy level could be used as an alternative to estimate leaf tissue N in the absence of leaf spectral information. The relationship between TCCScene and leaf tissue N was the lowest (r2 = 0.50), indicating that the estimation of canopy greenness from scene measurements needs improvement. In general, TCCLeaf and TCCCanopy performed better than the indices developed through correlation analysis and NDVI in discriminating the effects of N rates. Results from this study confirmed the potential of these indices as efficient methods for estimating in-season leaf N status of cotton.