Multiresolution techniques for audio signal restoration

This thesis describes a study of techniques for the restoration of musical audio signals using a multiresolution signal representation called the multiresolution Fourier transform (MFT), a time-frequency-scale representation. This representation allows the restoration to adapt to the local signal structure, which typically consists of a set of approximately sinusoidal partials, each consisting of an “onset” of rapid energy variation followed by more slowly varying “sustain” and “decay” phases. It must be decided what components of a noisy audio signal are to be kept in the restored version and, conversely, which must be removed. A simple filter is introduced that retains only musical signal —that is signal which adheres to the musical model — and rejects everything else. It is shown that this filter used in conjunction with the MIT has a low computational complexity. The MIT is used to capture the transient energy present at the onset of notes by splitting the time axis of a musical signal into steady-state and transient zones using a simple onset detector, which measures the expected energy at a given lime against the actual energy present. Past audio signal restoration systems have relied on estimating a restored audio signal’s spectrum from the noisy audio signal presented to the algorithm. In this thesis the idea of having more than one version of a recording is used in order to gain further information about the ideal spectrum of the noisy signal. This poses a number of problems with regards to matching the time scales of two versions of the same piece. These are addressed and solutions are offered, based on a novel multiresolution warping algorithm. Finally, various methods for using the detected signal spectrum of a clean modern signal to restore a noisy signal using the warping techniques and musical event detection filters are shown. These account for variations in scale and input signal to noise ratio (SNR) in the noisy signal. It is also shown how the simple adaptive filter introduced earlier can be used to restore audio signals with impulse noise as well as while additive noise. This filter and the time-warping technique is compared to adaptive Wiener filtering as an audio restoration method

Precursor Ion Independent Algorithm for Top-Down Shotgun Proteomics

We present a precursor ion independent top-down algorithm (PIITA) for use in automated assignment of protein identifications from tandem mass spectra of whole proteins. To acquire the data, we utilize data-dependent acquisition to select protein precursor ions eluting from a C4-based HPLC column for collision induced dissociation in the linear ion trap of an LTQ-Orbitrap mass spectrometer. Gas-phase fractionation is used to increase the number of acquired tandem mass spectra, all of which are recorded in the Orbitrap mass analyzer. To identify proteins, the PIITA algorithm compares deconvoluted, deisotoped, observed tandem mass spectra to all possible theoretical tandem mass spectra for each protein in a genomic sequence database without regard for measured parent ion mass. Only after a protein is identified, is any difference in measured and theoretical precursor mass used to identify and locate post-translation modifications. We demonstrate the application of PIITA to data generated via our wet-lab approach on a Salmonella typhimurium outer membrane extract and compare these results to bottom-up analysis. From these data, we identify 154 proteins by top-down analysis, 73 of which were not identified in a parallel bottom-up analysis. We also identify 201 unique isoforms of these 154 proteins at a false discovery rate (FDR) of <1%

Implications for constrained supersymmetry of combined H.E.S.S. observations of dwarf galaxies, the Galactic halo and the Galactic Centre

In order to place limits on dark matter (DM) properties using $\gamma$-ray observations, previous analyses have often assumed a very simple parametrisation of the $\gamma$-ray annihilation yield; typically, it has been assumed that annihilation proceeds through a single channel only. In realistic DM models, annihilation may occur into many different final states, making this quite a rough ansatz. With additional processes like virtual internal bremsstrahlung and final state radiation, this ansatz becomes even more incorrect, and the need for scans of explicit model parameter spaces becomes clear. Here we present scans of the parameter space of the Constrained Minimal Supersymmetric Standard Model (CMSSM), considering $\gamma$-ray spectra from three dwarf galaxies, the Galactic Centre region and the broader Galactic halo, as obtained with the High-Energy Stereoscopic System (H.E.S.S.). We present a series of likelihood scans combining the H.E.S.S. data with other experimental results. We show that observations of the Sagittarius, Carina and Sculptor dwarf galaxies disfavour the coannihilation region of the CMSSM and models with large annihilation cross-sections. This is true even under reasonable assumptions about the DM density profiles, and constitutes the strongest constraint to date on coannihilation models within the CMSSM. The Galactic halo has a similar, but weaker, effect. The Galactic Centre search is complicated by a strong (unknown) $\gamma$-ray source, and we see no effect on the CMSSM parameter space when assuming a realistic Galactic Centre DM density profile.Comment: 18 pages, 10 figures Major changes: added H.E.S.S. results on halo and two additional dwarf galaxies, title, abstract and text changed accordingl

Statistical coverage for supersymmetric parameter estimation: a case study with direct detection of dark matter

Models of weak-scale supersymmetry offer viable dark matter (DM) candidates. Their parameter spaces are however rather large and complex, such that pinning down the actual parameter values from experimental data can depend strongly on the employed statistical framework and scanning algorithm. In frequentist parameter estimation, a central requirement for properly constructed confidence intervals is that they cover true parameter values, preferably at exactly the stated confidence level when experiments are repeated infinitely many times. Since most widely-used scanning techniques are optimised for Bayesian statistics, one needs to assess their abilities in providing correct confidence intervals in terms of the statistical coverage. Here we investigate this for the Constrained Minimal Supersymmetric Standard Model (CMSSM) when only constrained by data from direct searches for dark matter. We construct confidence intervals from one-dimensional profile likelihoods and study the coverage by generating several pseudo-experiments for a few benchmark sets of pseudo-true parameters. We use nested sampling to scan the parameter space and evaluate the coverage for the benchmarks when either flat or logarithmic priors are imposed on gaugino and scalar mass parameters. The sampling algorithm has been used in the configuration usually adopted for exploration of the Bayesian posterior. We observe both under- and over-coverage, which in some cases vary quite dramatically when benchmarks or priors are modified. We show how most of the variation can be explained as the impact of explicit priors as well as sampling effects, where the latter are indirectly imposed by physicality conditions. For comparison, we also evaluate the coverage for Bayesian credible intervals, and observe significant under-coverage in those cases.Comment: 30 pages, 5 figures; v2 includes major updates in response to referee's comments; extra scans and tables added, discussion expanded, typos corrected; matches published versio

Learning an atlas of a cognitive process in its functional geometry

Proceedings of the 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011.In this paper we construct an atlas that captures functional characteristics of a cognitive process from a population of individuals. The functional connectivity is encoded in a low-dimensional embedding space derived from a diffusion process on a graph that represents correlations of fMRI time courses. The atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. The atlas is not directly coupled to the anatomical space, and can represent functional networks that are variable in their spatial distribution. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects.National Science Foundation (U.S.) (IIS/CRCNS 0904625)National Science Foundation (U.S.) (CAREER grant 0642971)National Institutes of Health (U.S.) (NCRR NAC P41- RR13218)National Institute of Biomedical Imaging and Bioengineering (U.S.) (U54-EB005149)National Institutes of Health (U.S.) (U41RR019703)National Institutes of Health (U.S.) (P01CA067165)Seventh Framework Programme (European Commission) (n◦257528 (KHRESMOI)

Digital Simulation for Automobile Maneuvers

A new all-digital simulation of automobile handling allows severe maneuvers involving braking or accel eration and cornering. A novel feature is the in corporation of closed-loop control based on a mathematical model of the human driver. The program is modular and well-documented. The model includes provisions for nonlinear tire and suspension forces and moments; it also allows the user to switch off the nonlinearities and to include an antilock brake system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68886/2/10.1177_003754978103700304.pd

The Five Factor Model of personality and evaluation of drug consumption risk

The problem of evaluating an individual's risk of drug consumption and misuse is highly important. An online survey methodology was employed to collect data including Big Five personality traits (NEO-FFI-R), impulsivity (BIS-11), sensation seeking (ImpSS), and demographic information. The data set contained information on the consumption of 18 central nervous system psychoactive drugs. Correlation analysis demonstrated the existence of groups of drugs with strongly correlated consumption patterns. Three correlation pleiades were identified, named by the central drug in the pleiade: ecstasy, heroin, and benzodiazepines pleiades. An exhaustive search was performed to select the most effective subset of input features and data mining methods to classify users and non-users for each drug and pleiad. A number of classification methods were employed (decision tree, random forest, $k$-nearest neighbors, linear discriminant analysis, Gaussian mixture, probability density function estimation, logistic regression and na{\"i}ve Bayes) and the most effective classifier was selected for each drug. The quality of classification was surprisingly high with sensitivity and specificity (evaluated by leave-one-out cross-validation) being greater than 70\% for almost all classification tasks. The best results with sensitivity and specificity being greater than 75\% were achieved for cannabis, crack, ecstasy, legal highs, LSD, and volatile substance abuse (VSA).Comment: Significantly extended report with 67 pages, 27 tables, 21 figure

Predicting Activation Across Individuals with Resting-State Functional Connectivity Based Multi-Atlas Label Fusion

The alignment of brain imaging data for functional neuroimaging studies is challenging due to the discrepancy between correspondence of morphology, and equivalence of functional role. In this paper we map functional activation areas across individuals by a multi-atlas label fusion algorithm in a functional space. We learn the manifold of resting-state fMRI signals in each individual, and perform manifold alignment in an embedding space. We then transfer activation predictions from a source population to a target subject via multi-atlas label fusion. The cost function is derived from the aligned manifolds, so that the resulting correspondences are derived based on the similarity of intrinsic connectivity architecture. Experiments show that the resulting label fusion predicts activation evoked by various experiment conditions with higher accuracy than relying on morphological alignment. Interestingly, the distribution of this gain is distributed heterogeneously across the cortex, and across tasks. This offers insights into the relationship between intrinsic connectivity, morphology and task activation. Practically, the mechanism can serve as prior, and provides an avenue to infer task-related activation in individuals for whom only resting data is available. Keywords: Functional Connectivity, Cortical Surface, Task Activation, Target Subject, Intrinsic ConnectivityCongressionally Directed Medical Research Programs (U.S.) (Grant PT100120)Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (R01HD067312)Neuroimaging Analysis Center (U.S.) (P41EB015902)Oesterreichische Nationalbank (14812)Oesterreichische Nationalbank (15929)Seventh Framework Programme (European Commission) (FP7 2012-PIEF-GA-33003

A Study of the \eta \pi^{0} Spectrum and Search for a J^{PC} = 1^{-+} Exotic Meson

A partial wave analysis (PWA) of the of the $\eta \pi ^0$ system (where $\eta \to \gamma \gamma$) produced in the charge exchange reaction $\pi ^-p\to \eta \pi ^0n$ at an incident momentum of 18 GeV$/c$ is presented as a function of ${\eta \pi ^0}$ invariant mass, $m_{\eta\pi^0}$, and momentum transfer squared, $t_{\pi^{-}\to\eta\pi}$, from the incident $\pi^-$ to the outgoing ${\eta\pi ^0}$ system. $S$, $P$ and $D$ waves were included in the PWA. The $a_0(980)$ and $a_2(1320)$ states are clearly observed in the overall ${\eta\pi ^0}$ effective mass distribution as well as in the amplitudes associated with $S$ wave and $D$ waves respectively after partial wave decomposition. The observed distributions in moments (averages of spherical harmonics) were compared to the results from the PWA and the two are consistent. The distribution in $t_{\pi^{-}\to\eta\pi}$ for individual $D$ waves associated with natural and unnatural parity exchange in the $t$-channel are consistent with Regge phenomenology. Of particular interest in this study is the $P$ wave since this leads to an exotic $J^{PC}=1^{-+}$ for the $\eta \pi$ system. A $P$ wave is present in the data, however attempts to describe the mass dependence of the amplitude and phase motion with respect to the $D$ wave as a Breit-Wigner resonance are problematic. This has implications regarding the existence of a reported exotic $J^{PC} = 1^{-+}$ meson decaying into $\eta \pi^0$ with a mass near 1.4 GeV$/c^2$.Comment: 19 pages, 29 figures, to appear in Phys. Rev.

Non-minimal kinetic coupling and Chaplygin gas cosmology

In the frame of the scalar field model with non minimal kinetic coupling to gravity, we study the cosmological solutions of the Chaplygin gas model of dark energy. By appropriately restricting the potential, we found the scalar field, the potential and coupling giving rise to the Chaplygin gas solution. Extensions to the generalized and modified Chaplygin gas have been made.Comment: 18 pages, 2 figures. To appear in EPJ