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Detection of Auditory Cortex Activity by fMRI Using a Dependent Component Analysis

ESTOMBELO-MONTESCO, Carlos A.; STURZBECHER, Marcio Jr.; BARROS, Allan K. D.; ARAUJO, Draulio B. de
Fonte: SPRINGER-VERLAG BERLIN Publicador: SPRINGER-VERLAG BERLIN
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
65.72%
Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM)...

Representações hierárquicas de vocábulos de línguas indígenas brasileiras: modelos baseados em mistura de Gaussianas; Hierarchical representations of words of brazilian indigenous languages: models based on Gaussian mixture

Sepúlveda Torres, Lianet
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 08/12/2010 Português
Relevância na Pesquisa
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Apesar da ampla diversidade de línguas indígenas no Brasil, poucas pesquisas estudam estas línguas e suas relações. Inúmeros esforços têm sido dedicados a procurar similaridades entre as palavras das línguas indígenas e classificá-las em famílias de línguas. Seguindo a classificação mais aceita das línguas indígenas do Brasil, esta pesquisa propõe comparar palavras de 10 línguas indígenas brasileiras. Para isso, considera-se que estas palavras são sinais de fala e estima-se a função de distribuição de probabilidade (PDF) de cada palavra, usando um modelo de mistura de gaussianas (GMM). A PDF foi considerada um modelo para representar as palavras. Os modelos foram comparados utilizando medidas de distância para construir estruturas hierárquicas que evidenciaram possíveis relações entre as palavras. Seguindo esta linha, a hipótese levantada nesta pesquisa é que as PDFs baseadas em GMM conseguem caracterizar as palavras das línguas indígenas, permitindo o emprego de medidas de distância entre elas para estabelecer relações entre as palavras, de forma que tais relações confirmem algumas das classificações. Os parâmetros do GMM foram calculados utilizando o algoritmo Maximização da Expectância (em inglês...

Decomposição de sinais eletromiográficos de superfície misturados linearmente utilizando análise de componentes independentes; Decomposition of linearly mixed surface electromyographic signals using independent component analysis

Tiago Paggi de Almeida
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 13/06/2012 Português
Relevância na Pesquisa
45.64%
A eletromiografia e uma pratica clinica que permite inferir sobre a integridade do sistema neuromuscular, o que inclui a analise da unidade funcional contrátil do sistema neuromuscular, a unidade motora. O sinal eletromiografico e um sinal elétrico resultante do transiente iônico devido potenciais de ação de unidades motoras capturados por eletrodos invasivos ou não invasivos. Eletrodos invasivos capturam potenciais de ação de ate uma única unidade motora, porem o procedimento e demorado e incomodo. Eletrodos de superfície permitem detectar potenciais de ação de modo não invasivo, porem resultam na mistura de potenciais de ação de varias unidades motoras, resultando em um sinal com aparência de ruído aleatório, dificultando uma analise. Técnicas de Separação Cega de Fontes, como Analise de Componentes Independentes, tem se mostrado eficientes na decomposição de sinais eletromiograficos de superfície nos constituintes potenciais de ação de unidades motoras. Este projeto tem como objetivo desenvolver um protótipo capaz de capturar sinais mioeletricos de superfície e analisar a viabilidade da separação de sinais eletromiograficos intramusculares misturados linearmente, utilizando Analise de Componentes Independentes. O sistema proposto integra uma matriz de eletrodos com ate sete canais...

Decomposition of a mixture of signals in a model of the olfactory bulb.

Hendin, O; Horn, D; Hopfield, J J
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 21/06/1994 Português
Relevância na Pesquisa
55.51%
We describe models for the olfactory bulb which perform separation and decomposition of mixed odor inputs from different sources. The odors are unknown to the system; hence this is an analog and extension of the engineering problem of blind separation of signals. The separation process makes use of the different temporal fluctuations of the input odors which occur under natural conditions. We discuss two possibilities, one relying on a specific architecture connecting modules with the same sensory inputs and the other assuming that the modules (e.g., glomeruli) have different receptive fields in odor space. We compare the implications of these models for the testing of mixed odors from a single source.

Six Peptide Wound Signals Derived from a Single Precursor Protein in Ipomoea batatas Leaves Activate the Expression of the Defense Gene Sporamin*

Chen, Yu-Chi; Siems, William F.; Pearce, Gregory; Ryan, Clarence A.
Fonte: American Society for Biochemistry and Molecular Biology Publicador: American Society for Biochemistry and Molecular Biology
Tipo: Artigo de Revista Científica
Publicado em 25/04/2008 Português
Relevância na Pesquisa
45.56%
A mixture of three homologous bioactive hydroxyproline-rich glycopeptides (HypSys peptides) of 18 amino acids in length, differing only at two residues, was isolated from leaves of Ipomoea batatas, the common sweet potato. One of the peptides represented over 95% of the isolated isopeptides, which, at 2.5 nm concentration, induced the expression of sporamin, a major defense protein of I. batatas. The sequence of the major isoform was used to synthesize a primer that identified a cDNA encoding a precursor protein. The protein contained six proline-rich regions whose sequences suggested that they might be HypSys defense signals. One of the encoded peptides, called IbHypSys IV, was identical to one of two minor components of the isolated isopeptides, but neither the major isopeptide nor the other minor isoform was found within the precursor. The six peptides encoded by the precursor gene were synthesized but with hydroxyproline residues at positions found in the native isoforms and lacking carbohydrate moieties. All of the peptides were biologically active when supplied to leaves of sweet potato plants. The gene is the first ortholog of the preproHypSys gene family to be found outside of the Solanaceae family, and its encoded peptide precursor is the first example in plants of a precursor protein with six potential peptide defense signals...

Independent Vector Analysis for Source Separation Using a Mixture of Gaussians Prior

Hao, Jiucang; Lee, Intae; Lee, Te-Won; Sejnowski, Terrence J.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /06/2010 Português
Relevância na Pesquisa
45.66%
Convolutive mixtures of signals, which are common in acoustic environments, can be difficult to separate into their component sources. Here we present a uniform probabilistic framework to separate convolutive mixtures of acoustic signals using independent vector analysis (IVA), which is based on a joint distribution for the frequency components originating from the same source and is capable of preventing permutation disorder. Different gaussian mixture models (GMM) served as source priors, in contrast to the original IVA model, where all sources were modeled by identical multivariate Laplacian distributions. This flexible source prior enabled the IVA model to separate different type of signals. Three classes of models were derived and tested: noiseless IVA, online IVA, and noisy IVA. In the IVA model without sensor noise, the unmixing matrices were efficiently estimated by the expectation maximization (EM) algorithm. An online EM algorithm was derived for the online IVA algorithm to track the movement of the sources and separate them under nonstationary conditions. The noisy IVA model included the sensor noise and combined denoising with separation. An EM algorithm was developed that found the model parameters and separated the sources simultaneously. These algorithms were applied to separate mixtures of speech and music. Performance as measured by the signal-to-interference ratio (SIR) was substantial for all three models.

Formation of 7-carboxyheptyl radical induced by singlet oxygen in the reaction mixture of oleic acid, riboflavin and ferrous ion under the UVA irradiation

Mori, Hiroko; Iwahashi, Hideo
Fonte: the Society for Free Radical Research Japan Publicador: the Society for Free Radical Research Japan
Tipo: Artigo de Revista Científica
Português
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45.61%
Identification of the radicals was performed for the standard reaction mixtures, which contained 4.3 mM oleic acid, 25 µM riboflavin, 1 mM FeSO4(NH4)2SO4, 10 mM cholic acid, 40 mM phosphate buffer (pH 7.4) and 0.1 M α-(4-pyridyl-1-oxide)-N-tert-butylnitrone under the UVA irradiation (365 nm), using an electron spin resonance, an high performance liquid chromatography-electron spin resonance and an high performance liquid chromatography-electron spin resonance-mass spectrometry. The electron spin resonance and high performance liquid chromatography-electron spin resonance measurements of the standard reaction mixtures showed prominent signals (αN = 1.58 mT and αHβ = 0.26 mT) and peaks 1 and 3 (retention times, 37.0 min and 49.0 min). Since the peak 3 was not observed for the standard reaction mixture without oleic acid, the radical of the peak 3 seems to be derived from oleic acid. Singlet oxygens seem to participate in the formation of the oleic acid-derived radicals because the peak height of the peak 3 observed in the standard reaction mixture of D2O increased to 308 ± 72% of the control. The high performance liquid chromatography-electron spin resonance-mass spectrometry analysis showed that 7-carboxyheptyl radical forms in the standard reaction mixture.

Fourier domain pump-probe optical coherence tomography imaging of Melanin

Jacob, Desmond; Shelton, Ryan L.; Applegate, Brian E.
Fonte: Optical Society of America Publicador: Optical Society of America
Tipo: Artigo de Revista Científica
Publicado em 26/05/2010 Português
Relevância na Pesquisa
45.53%
We report the development of a two-color Fourier domain Pump-Probe Optical Coherence Tomography (PPOCT) system. Tissue phantom experiments to characterize the system performance demonstrated imaging depths in excess of 725 μm, nearly comparable to the base Optical Coherence Tomography system. PPOCT A-line rates were also demonstrated in excess of 1 kHz. The physical origin of the PPOCT signal was investigated with a series of experiments which revealed that the signal is a mixture of short and long lifetime component signals. The short lifetime component was attributed to transient absorption while the long lifetime component may be due to a mixture of transient absorption and thermal effects. Ex vivo images of porcine iris demonstrated the potential for imaging melanin in the eye, where cancer of the melanocytes is the most common form of eye cancer in adults.

In vitro reconstitution of lipid-dependent dual topology and postassembly topological switching of a membrane protein

Vitrac, Heidi; Bogdanov, Mikhail; Dowhan, William
Fonte: National Academy of Sciences Publicador: National Academy of Sciences
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.52%
Phospholipids could exert their effect on membrane protein topology either directly by interacting with topogenic signals of newly inserted proteins or indirectly by influencing the protein assembly machinery. In vivo lactose permease (LacY) of Escherichia coli displays a mixture of topological conformations ranging from complete inversion of the N-terminal helical bundle to mixed topology and then to completely native topology as phosphatidylethanolamine (PE) is increased from 0% to 70% of membrane phospholipids. These topological conformers are interconvertible by postassembly synthesis or dilution of PE in vivo. To investigate whether coexistence of multiple topological conformers is dependent solely on the membrane lipid composition, we determined the topological organization of LacY in an in vitro proteoliposome system in which lipid composition can be systematically controlled before (liposomes) and after (fliposomes) reconstitution using a lipid exchange technique. Purified LacY reconstituted into preformed liposomes of increasing PE content displayed inverted topology at low PE and then a mixture of inverted and proper topologies with the latter increasing with increasing PE until all LacY adopted its native topology. Interconversion between topological conformers of LacY was observed in a PE dose-dependent manner by either increasing or decreasing PE levels in proteoliposomes postreconstitution of LacY...

Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds

Chen, Minhua; Silva, Jorge; Paisley, John; Wang, Chunping; Dunson, David; Carin, Lawrence
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /12/2010 Português
Relevância na Pesquisa
45.58%
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x ∈ ℝN that are of high dimension N but are constrained to reside in a low-dimensional subregion of ℝN. The number of mixture components and their rank are inferred automatically from the data. The resulting algorithm can be used for learning manifolds and for reconstructing signals from manifolds, based on compressive sensing (CS) projection measurements. The statistical CS inversion is performed analytically. We derive the required number of CS random measurements needed for successful reconstruction, based on easily-computed quantities, drawing on block-sparsity properties. The proposed methodology is validated on several synthetic and real datasets.

Automatic NMR-Based Identification of Chemical Reaction Types in Mixtures of Co-Occurring Reactions

Latino, Diogo A. R. S.; Aires-de-Sousa, João
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 13/02/2014 Português
Relevância na Pesquisa
45.61%
The combination of chemoinformatics approaches with NMR techniques and the increasing availability of data allow the resolution of problems far beyond the original application of NMR in structure elucidation/verification. The diversity of applications can range from process monitoring, metabolic profiling, authentication of products, to quality control. An application related to the automatic analysis of complex mixtures concerns mixtures of chemical reactions. We encoded mixtures of chemical reactions with the difference between the 1H NMR spectra of the products and the reactants. All the signals arising from all the reactants of the co-occurring reactions were taken together (a simulated spectrum of the mixture of reactants) and the same was done for products. The difference spectrum is taken as the representation of the mixture of chemical reactions. A data set of 181 chemical reactions was used, each reaction manually assigned to one of 6 types. From this dataset, we simulated mixtures where two reactions of different types would occur simultaneously. Automatic learning methods were trained to classify the reactions occurring in a mixture from the 1H NMR-based descriptor of the mixture. Unsupervised learning methods (self-organizing maps) produced a reasonable clustering of the mixtures by reaction type...

The Subcortical Cocktail Problem; Mixed Signals from the Subthalamic Nucleus and Substantia Nigra

de Hollander, Gilles; Keuken, Max C.; Forstmann, Birte U.
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 20/03/2015 Português
Relevância na Pesquisa
45.62%
The subthalamic nucleus and the directly adjacent substantia nigra are small and important structures in the basal ganglia. Functional magnetic resonance imaging studies have shown that the subthalamic nucleus and substantia nigra are selectively involved in response inhibition, conflict processing, and adjusting global and selective response thresholds. However, imaging these nuclei is complex, because they are in such close proximity, they can vary in location, and are very small relative to the resolution of most fMRI sequences. Here, we investigated the consistency in localization of these nuclei in BOLD fMRI studies, comparing reported coordinates with probabilistic atlas maps of young human participants derived from ultra-high resolution 7T MRI scanning. We show that the fMRI signal reported in previous studies is likely not unequivocally arising from the subthalamic nucleus but represents a mixture of subthalamic nucleus, substantia nigra, and surrounding tissue. Using a simulation study, we also tested to what extent spatial smoothing, often used in fMRI preprocessing pipelines, influences the mixture of BOLD signals. We propose concrete steps how to analyze fMRI BOLD data to allow inferences about the functional role of small subcortical nuclei like the subthalamic nucleus and substantia nigra.

Advantages and Limitations of the Use of Optogenetic Approach in Studying Fast-Scale Spike Encoding

Malyshev, Aleksey; Goz, Roman; LoTurco, Joseph J.; Volgushev, Maxim
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 07/04/2015 Português
Relevância na Pesquisa
55.43%
Understanding single-neuron computations and encoding performed by spike-generation mechanisms of cortical neurons is one of the central challenges for cell electrophysiology and computational neuroscience. An established paradigm to study spike encoding in controlled conditions in vitro uses intracellular injection of a mixture of signals with fluctuating currents that mimic in vivo-like background activity. However this technique has two serious limitations: it uses current injection, while synaptic activation leads to changes of conductance, and current injection is technically most feasible in the soma, while the vast majority of synaptic inputs are located on the dendrites. Recent progress in optogenetics provides an opportunity to circumvent these limitations. Transgenic expression of light-activated ionic channels, such as Channelrhodopsin2 (ChR2), allows induction of controlled conductance changes even in thin distant dendrites. Here we show that photostimulation provides a useful extension of the tools to study neuronal encoding, but it has its own limitations. Optically induced fluctuating currents have a low cutoff (~70Hz), thus limiting the dynamic range of frequency response of cortical neurons. This leads to severe underestimation of the ability of neurons to phase-lock their firing to high frequency components of the input. This limitation could be worked around by using short (2 ms) light stimuli which produce membrane potential responses resembling EPSPs by their fast onset and prolonged decay kinetics. We show that combining application of short light stimuli to different parts of dendritic tree for mimicking distant EPSCs with somatic injection of fluctuating current that mimics fluctuations of membrane potential in vivo...

Large vocabulary continuous speech recognition using linguistic features and constraints

Tang, Min, Ph. D. Massachusetts Institute of Technology
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 123 leaves; 777354 bytes; 732301 bytes; application/pdf; application/pdf
Português
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45.55%
Automatic speech recognition (ASR) is a process of applying constraints, as encoded in the computer system (the recognizer), to the speech signal until ambiguity is satisfactorily resolved to the extent that only one sequence of words is hypothesized. Such constraints fall naturally into two categories. One deals with the ordering of words (syntax) and organization of their meanings (semantics, pragmatics, etc). The other governs how speech signals are related to words, a process often termed as lexical access". This thesis studies the Huttenlocher-Zue lexical access model, its implementation in a modern probabilistic speech recognition framework and its application to continuous speech from an open vocabulary. The Huttenlocher-Zue model advocates a two-pass lexical access paradigm. In the first pass, the lexicon is effectively pruned using broad linguistic constraints. In the original Huttenlocher-Zue model, the authors had proposed six linguistic features motivated by the manner of pronunciation. The first pass classifies speech signals into a sequence of linguistic features, and only words that match this sequence - the cohort - are activated. The second pass performs a detailed acoustic phonetic analysis within the cohort to decide the identity of the word. This model differs from the lexical access model nowadays commonly employed in speech recognizers where detailed acoustic phonetic analysis is performed directly and lexical items are retrieved in one pass. The thesis first studies the implementation issues of the Huttenlocher-Zue model. A number of extensions to the original proposal are made to take advantage of the existing facilities of a probabilistic...

Development of high-speed two-photon microscopy for biological and medical applications

Kim, Ki Hean
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 144 p.
Português
Relevância na Pesquisa
55.42%
Two-photon microscopy (TPM) is one of the most powerful microscopic technologies for in-vivo 3D tissue imaging up to a few hundred micrometers. It has been finding important applications in neuronal imaging, tumor physiology study, and optical biopsy. A practical limitation of TPM is its slow imaging speed (0.3 1 frames/s). We designed high-speed two-photon microscopes (HSTPMs) whose imaging speed is more than 10 times faster than traditional TPM, while their imaging depths, image contrast are comparable to those of TPM. The first high speed system is HSTPM based on polygonal mirror scanner. The scanning speed reaches 13 frames/s for typical tissues using a polygonal mirror scanner. This system is based on single-focus scanning and single-pixel signal collection. The usage of higher input power is required to compensate for the signal reduction due to higher scanning speed. However, since fluorescence signal is ultimately limited by the saturation of fluorophores due to their finite lifetimes, is the signal to noise ratio (SNR) of single focus scanning systems are also ultimately limited at high speed. This problem is circumvented in a second system based on parallelization by scanning specimens with multiple foci of excitation light and collecting signals with spatially resolved detectors. The imaging speed is increased proportional to the number of foci and similar excitation laser power per focus circumventing the problem of fluorophore saturation. However...

Combined-channel instantaneous frequency analysis for audio source separation based on comodulation

Jacobson, Barry David
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 303 p.
Português
Relevância na Pesquisa
45.55%
Normal human listeners have a remarkable ability to focus on a single sound or speaker of interest and to block out competing sound sources. Individuals with hearing impairments, on the other hand, often experience great difficulty in noisy environments. The goal of our research is to develop novel signal processing methods inspired by neural auditory processing that can improve current speech separation systems. These could potentially be of use as assistive devices for the hearing impaired, and in many other communications applications. Our focus is the monaural case where spatial information is not available. Much perceptual evidence indicates that detecting common amplitude and frequency variation in acoustic signals plays an important role in the separation process. The physical mechanisms of sound generation in many sources cause common onsets/offsets and correlated increases/decreases in both amplitude and frequency among the spectral components of an individual source, which can potentially serve as a distinct signature. However, harnessing these common modulation patterns is difficult because when spectral components of competing sources overlap within the bandwidth of a single auditory filter, the modulation envelope of the resultant waveform resembles that of neither source. To overcome this...

A Fourier-Prony Tauberian Approach to the Analysis of a Mixture of Delayed Signals

de Figueiredo, Rui J.P.; Hu, C.L.; de Figueiredo, Rui J.P.; Hu, C.L.
Fonte: Universidade Rice Publicador: Universidade Rice
Tipo: Relatório
Português
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45.57%
Tech Report; Let x and y be signals (i.e. real-valued functions of time) of finite duration and energy. In the present paper, we develop a frequency domain Prony approach for interpolating, or in general, approximating y(t) by ....

A Bayesian approach to the study of white dwarf binaries in LISA data: The application of a reversible jump Markov chain Monte Carlo method

Stroeer, Alexander; Veitch, John
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
45.62%
The Laser Interferometer Space Antenna (LISA) defines new demands on data analysis efforts in its all-sky gravitational wave survey, recording simultaneously thousands of galactic compact object binary foreground sources and tens to hundreds of background sources like binary black hole mergers and extreme mass ratio inspirals. We approach this problem with an adaptive and fully automatic Reversible Jump Markov Chain Monte Carlo sampler, able to sample from the joint posterior density function (as established by Bayes theorem) for a given mixture of signals "out of the box'', handling the total number of signals as an additional unknown parameter beside the unknown parameters of each individual source and the noise floor. We show in examples from the LISA Mock Data Challenge implementing the full response of LISA in its TDI description that this sampler is able to extract monochromatic Double White Dwarf signals out of colored instrumental noise and additional foreground and background noise successfully in a global fitting approach. We introduce 2 examples with fixed number of signals (MCMC sampling), and 1 example with unknown number of signals (RJ-MCMC), the latter further promoting the idea behind an experimental adaptation of the model indicator proposal densities in the main sampling stage. We note that the experienced runtimes and degeneracies in parameter extraction limit the shown examples to the extraction of a low but realistic number of signals.; Comment: 18 pages...

A Deterministic Analysis of an Online Convex Mixture of Expert Algorithms

Donmez, Mehmet A.; Tunc, Sait; Kozat, Suleyman S.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 27/09/2012 Português
Relevância na Pesquisa
45.71%
We analyze an online learning algorithm that adaptively combines outputs of two constituent algorithms (or the experts) running in parallel to model an unknown desired signal. This online learning algorithm is shown to achieve (and in some cases outperform) the mean-square error (MSE) performance of the best constituent algorithm in the mixture in the steady-state. However, the MSE analysis of this algorithm in the literature uses approximations and relies on statistical models on the underlying signals and systems. Hence, such an analysis may not be useful or valid for signals generated by various real life systems that show high degrees of nonstationarity, limit cycles and, in many cases, that are even chaotic. In this paper, we produce results in an individual sequence manner. In particular, we relate the time-accumulated squared estimation error of this online algorithm at any time over any interval to the time accumulated squared estimation error of the optimal convex mixture of the constituent algorithms directly tuned to the underlying signal in a deterministic sense without any statistical assumptions. In this sense, our analysis provides the transient, steady-state and tracking behavior of this algorithm in a strong sense without any approximations in the derivations or statistical assumptions on the underlying signals such that our results are guaranteed to hold. We illustrate the introduced results through examples.; Comment: arXiv admin note: substantial text overlap with arXiv:1203.4209

Natural-Abundance C13 Nuclear Magnetic Resonance Spectra of Medium-Molecular-Weight Organic Compounds

Weigert, Frank J.; Jautelat, Manfred; Roberts, John D.
Fonte: National Academy of Sciences Publicador: National Academy of Sciences
Tipo: Article; PeerReviewed Formato: application/pdf
Publicado em /08/1968 Português
Relevância na Pesquisa
45.56%
The difficulties in detection of C13 magnetic resonance signals in organic compounds which arise from the low natural abundance and the small magnetic moment of C13 are well known [1]. For complex substances of biochemical interest, further reduction in signal-to-noise ratio occurs because of extensive carbon-proton spin-spin interactions. Considerable relief from these difficulties is possible in principle with complete proton decoupling that enhances the signals by removing the proton splittings and contributing a favorable Overhauser effect [2]. The problem with proton decoupling as ordinarily practiced is the necessity for extensive variations in the decoupling frequency to locate the proper values for sharp decoupling of all of the carbon resonances. If the C13 signals are already so weak as to require enhancement by time averaging with repetitive scans [3], excessively long scanning times may be necessary to obtain satisfactory spectra. Some idea of what is involved, in a rather favorable case, may be seen from Figure 1, which shows a series of C13 spectra of a mixture of α- and β-pinenes run with four different proton decoupling frequencies with the use of the DFS spectrometer previously described [3,4]. Although the power input at the decoupling frequencies chosen was close to the maximum that could be supplied to the oscillator coil...