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Academic literature on the topic 'Signals’ analysis methods'

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Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Signals’ analysis methods"

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Ngui, Wai Keng, M. Salman Leong, Lim Meng Hee, and Ahmed M. Abdelrhman. "Wavelet Analysis: Mother Wavelet Selection Methods." Applied Mechanics and Materials 393 (September 2013): 953–58. http://dx.doi.org/10.4028/www.scientific.net/amm.393.953.

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Wavelet analysis, being a popular time-frequency analysis method has been applied in various fields to analyze a wide range of signals covering biological signals, vibration signals, acoustic and ultrasonic signals, to name a few. With the capability to provide both time and frequency domains information, wavelet analysis is mainly for time-frequency analysis of signals, signal compression, signal denoising, singularity analysis and features extraction. The main challenge in using wavelet transform is to select the most optimum mother wavelet for the given tasks, as different mother wavelet applied on to the same signal may produces different results. This paper reviews on the mother wavelet selection methods with particular emphasis on the quantitative approaches. A brief description of the proposed new technique to determine the optimum mother wavelet specifically for machinery faults diagnosis is also presented in this paper.
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Qu, Yanhuai, Shuai Zhang, and Qingkai Han. "Comparison of Non-linear Signals Analysis Methods." MATEC Web of Conferences 232 (2018): 01014. http://dx.doi.org/10.1051/matecconf/201823201014.

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In modern engineering, linear is relative, while non-linear and non-stationary is absolute. There are many methods in non-linear signals processing. How to select a most suitable analysis method quickly for the nonlinear signal is particularly important, which can improve the signal processing efficiently. In this paper, three common analysis methods for nonlinear signals, Wavelet spectrum, Hilbert spectral analysis (HSA) and Poincaré mapping are researched and analyzed by some typical nonlinear signals from the complex electromechanical model test system. The effectiveness and application scopes of these approaches are obtained, which can provide a theoretical and practical basis for engineering application.
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Garg, Malika. "Methods for the Analysis of EEG signals: A Review." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (September 30, 2021): 873–76. http://dx.doi.org/10.22214/ijraset.2021.38072.

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Abstract: Electroencephalography (EEG) helps to predict the state of the brain. It tells about the electrical activity going on in the brain. Difference of the surface potential evolved from various activities get recorded as EEG. The analysis of these EEG signals is of utmost importance to solve the problems related to the brain. Signal pre-processing, feature extraction and classification are the main steps of the EEG signal analysis. In this article we discussed various processing techniques of EEG signals. Keywords: EEG, analysis, signal processing, feature extraction, classification
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Muthuswamy, Jitendran, and Nitish V. Thakor. "Spectral analysis methods for neurological signals." Journal of Neuroscience Methods 83, no. 1 (August 1998): 1–14. http://dx.doi.org/10.1016/s0165-0270(98)00065-x.

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A, Mohammed. "Deconvolution methods for biomedical signals analysis." Indian Journal of Science and Technology 3, no. 2 (February 20, 2010): 105–9. http://dx.doi.org/10.17485/ijst/2010/v3i2.1.

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Musha, Takaaki, and Tatsuya Kumazawa. "Intensity analysis methods for transient signals." Applied Acoustics 69, no. 1 (January 2008): 60–67. http://dx.doi.org/10.1016/j.apacoust.2006.08.011.

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Debbal, S. M. "Pathological Electromyogram (EMG) Signal Analysis Parameters." Clinical Cardiology and Cardiovascular Interventions 4, no. 13 (August 9, 2021): 01–14. http://dx.doi.org/10.31579/2641-0419/185.

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Clinical analysis of the electromyogram is a powerful tool for diagnosis of neuromuscular diseases. There fore, the detection and the analysis of electromyogram signals has he attracted much attention over the years. Several methods based on modern signal Processing techniques such as temporal analysis, spectro-temporel analysis ..., have been investigated for electromyogram signal treatment. However, many of these analysis methods are not highly successful due to their complexity and non-stationarity. The aim of this study is to analyse the EMGs signals using nonlinear analysis. This analysis can provide a wide range of information’s related to the type of signal (normal and pathological).
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Iwaniec, Joanna, Marek Iwaniec, and Antoni Kalukiewicz. "Application of vectorcardiography and recurrence-based methods to analysis of ECG signals." MATEC Web of Conferences 241 (2018): 01015. http://dx.doi.org/10.1051/matecconf/201824101015.

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The paper concerns application of vectorcardiography and recurrence-based methods to analyze ECG signals. The first method involves recording the direction and magnitude of electrical forces of the heart by means of a continuous series of vectors that form a curving line around a center, while the second consists in representing the ECG signals in the phase space and searching for the recurrence properties of the registered signals. In both methods, change of analysis domain offers new opportunities for early diagnosis. In this work, discussed methods have been used for the purposes of analysis of selected ECG signals stored in the medical database. Vectorcardiograms were determined on the basis of ECG signals for the Farnk's leads. Signal analysis was carried out with the application of the recurrence plots (RP) method. The proposed approach simplifies assessment of the signal information content by providing patterns characteristic for different myocardial injury. Carried out research requires complementation by results of statistical analysis for various age groups and degrees of myocardial injury.
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Nam, Ki Woo, Seok Hwan Ahn, and Jin Wook Kim. "Nondestructive Evaluation in Materials Using Time-Frequency Analysis Methods." Key Engineering Materials 297-300 (November 2005): 2090–95. http://dx.doi.org/10.4028/www.scientific.net/kem.297-300.2090.

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Application of signal processing techniques to nondestructive evaluation (NDE) in general has become a standard tool in determining the frequency characteristics of the signals and relating these characteristics to the integrity of the structure under consideration. The joint time-frequency analysis techniques are applied to analyze ultrasonic signals in degraded austenite stainless 316 steel, to study the evaluation of damage in this material. It is demonstrated that the nonstationary characteristics of ultrasonic signals could be analyzed effectively by these methods. WVD was found to be more effective for analyzing the attenuation and frequency characteristics of degraded materials through ultrasonic. It is indicated that the time-frequency analysis methods should also be useful in evaluating various damages and defects in structural members.
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Gao, Yuan Sheng, Qiang Chen, Qiang Sun, Zhong Chen, and Wen Hai Zhang. "The Impedance Calculation Methods Using Damped Sinusoidal Signal." Advanced Materials Research 860-863 (December 2013): 2003–6. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.2003.

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There are large number of transient signals will be produced when the operation mode is changed. And the frequency of the transient signals distributed in wide range. The most of them are damped and oscillated. The impedance is a popular feature in power system, and it has been widely used in relay protection and fault location. So the impedance calculation based on the damped sinusoidal signal have been the important way to diagnosis the fault, locate the fault and so on. But the methods used now are based on the fundamental impedance calculation theory, lacking theoretical basis. In fact, the traditional methods for fundamental signal calculation are not appropriate for the quantitative analysis of damped sinusoidal signal. The paper analyzed the impedance calculation based on damped sinusoidal signal, combined the features of damped sinusoidal signals and the traditional impedance calculation method. The two typical signal analysis methods for damped sinusoidal signal extraction are used to calculate the accurate impedance based on the different extraction results. And the analysis laid a foundation for the impedance calculation using damped sinusoidal signals.
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Dissertations / Theses on the topic "Signals’ analysis methods"

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Sava, Herkole P. "Spectral analysis of phonocardiographic signals using advanced parametric methods." Thesis, University of Edinburgh, 1995. http://hdl.handle.net/1842/12903.

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The research detailed in this thesis investigates the performance of several advanced signal processing techniques when analysis heart sound, and investigates the feasibility of such a method for monitoring the condition of bioprosthetic heart valves. A data-acquisition system was designed which records and digitises heart sounds in a wide variety of cases ranging from sounds produced by native heart valves to mechanical prosthetic heart values. Heart sounds were recorded from more than 150 patients including subjects with normal and abnormal native, bioprosthetic, and mechanical prosthetic heart values. The acquired sounds were pre-processed in order to extract the signal of interest. Various spectral estimation techniques were investigated with a view to assessing the performance and suitability of these methods when analysing the first and second heart sounds. The performance of the following methods is analysed: the classical Fourier transform, autoregressive modelling based on two different approaches, autoregressive-moving average modelling, and Prony's spectral method. In general, it was also found that all parametric methods based on the singular value decomposition technique produce a more accurate spectral representation than the conventional methods (i.e. Fourier transform and autoregressive modelling) in terms of spectral resolution. Among these, the Prony's method is the best. In addition a modified forward-backward overdetermined Prony's algorithm is proposed for analysing heart sounds which produces an improvement of more than 10% over previous methods in terms of normalised mean-square error. Furthermore, a new method for estimating the model order is proposed for the case of heart sounds based on the distribution of the eigenvalues of the data matrix.
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Balli, Tugce. "Nonlinear analysis methods for modelling of EEG and ECG signals." Thesis, University of Essex, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.528852.

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Pham, Duong Hung. "Contributions to the analysis of multicomponent signals : synchrosqueezing and associated methods." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAM044/document.

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De nombreux signaux physiques incluant des signaux audio (musique, parole), médicaux (ECG, PCG), de mammifères marins ou d'ondes gravitationnelles peuvent être modélisés comme une superposition d'ondes modulées en amplitude et en fréquence (modes AM-FM), appelés signaux multicomposantes (SMCs). L'analyse temps-fréquence (TF) joue un rôle central pour la caractérisation de tels signaux et, dans ce cadre, diverses méthodes ont été développées au cours de la dernière décennie. Néanmoins, ces méthodes souffrent d'une limitation intrinsèque appelée le principe d'incertitude. Dans ce contexte, la méthode de réallocation (MR) a été développée visant à améliorer les représentations TF (RTFs) données respectivement par la transformée de Fourier à court terme (TFCT) et la transformée en ondelette continue (TOC), en les concentrant autour des lignes de crête correspondant aux fréquences instantanées. Malheureusement, elle ne permet pas de reconstruction des modes, contrairement à sa variante récente connue sous le nom de transformée synchrosqueezée (TSS). Toutefois, de nombreux problèmes associés à cette dernière restent encore à traiter tels que le traitement des fortes modulations en fréquence, la reconstruction des modes d'un SMC à partir de sa TFCT sous-échantillonnée or l'estimation des signatures TF de modes irréguliers et discontinus. Cette thèse traite principalement de tels problèmes afin de construire des nouvelles méthodes TF inversibles plus puissantes et précises pour l'analyse des SMCs.Cette thèse offre six nouvelles contributions précieuses. La première contribution introduit une extension de TSS d'ordre deux appliqué à la TOC ainsi qu'une discussion sur son analyse théorique et sa mise en œuvre pratique. La seconde contribution propose une généralisation des techniques de synchrosqueezing construites sur la TFCT, connue sous le nom de transformée synchrosqueezée d'ordre supérieur (FTSSn), qui permet de mieux traiter une large gamme de SMCs. La troisième contribution propose une nouvelle technique utilisant sur la transformée synchrosqueezée appliquée à la TFCT de second ordre (FTSS2) et une procédure de démodulation, appelée DTSS2, conduisant à une meilleure performance de la reconstruction des modes. La quatrième contribution est celle d'une nouvelle approche permettant la récupération des modes d'un SMC à partir de sa TFCT sous-échantillonnée. La cinquième contribution présente une technique améliorée, appelée calcul de représentation des contours adaptatifs (CRCA), utilisée pour une estimation efficace des signatures TF d'une plus grande classe de SMCs. La dernière contribution est celle d'une analyse conjointe entre l'CRCA et la factorisation matricielle non-négative (FMN) pour un débruitage performant des signaux phonocardiogrammes (PCG)
Many physical signals including audio (music, speech), medical data (ECG, PCG), marine mammals or gravitational-waves can be accurately modeled as a superposition of amplitude and frequency-modulated waves (AM-FM modes), called multicomponent signals (MCSs). Time-frequency (TF) analysis plays a central role in characterizing such signals and in that framework, numerous methods have been proposed over the last decade. However, these methods suffer from an intrinsic limitation known as the uncertainty principle. In this regard, reassignment method (RM) was developed with the purpose of sharpening TF representations (TFRs) given respectively by the short-time Fourier transform (STFT) or the continuous wavelet transform (CWT). Unfortunately, it did not allow for mode reconstruction, in opposition to its recent variant known as synchrosqueezing transforms (SST). Nevertheless, many critical problems associated with the latter still remain to be addressed such as the weak frequency modulation condition, the mode retrieval of an MCS from its downsampled STFT or the TF signature estimation of irregular and discontinuous signals. This dissertation mainly deals with such problems in order to provide more powerful and accurate invertible TF methods for analyzing MCSs.This dissertation gives six valuable contributions. The first one introduces a second-order extension of wavelet-based SST along with a discussion on its theoretical analysis and practical implementation. The second one puts forward a generalization of existing STFT-based synchrosqueezing techniques known as the high-order STFT-based SST (FSSTn) that enables to better handle a wide range of MCSs. The third one proposes a new technique established on the second-order STFT-based SST (FSST2) and demodulation procedure, called demodulation-FSST2-based technique (DSST2), enabling a better performance of mode reconstruction. The fourth contribution is that of a novel approach allowing for the retrieval of modes of an MCS from its downsampled STFT. The fifth one presents an improved method developed in the reassignment framework, called adaptive contour representation computation (ACRC), for an efficient estimation of TF signatures of a larger class of MCSs. The last contribution is that of a joint analysis of ACRC with non-negative matrix factorization (NMF) to enable an effective denoising of phonocardiogram (PCG) signals
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Lin, Chao. "P and T wave analysis in ECG signals using Bayesian methods." Phd thesis, Toulouse, INPT, 2012. http://oatao.univ-toulouse.fr/8990/1/lin.pdf.

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This thesis studies Bayesian estimation/detection algorithms for P and T wave analysis in ECG signals. In this work, different statistical models and associated Bayesian methods are proposed to solve simultaneously the P and T wave delineation task (determination of the positions of the peaks and boundaries of the individual waves) and the waveform-estimation problem. These models take into account appropriate prior distributions for the unknown parameters (wave locations and amplitudes, and waveform coefficients). These prior distributions are combined with the likelihood of the observed data to provide the posterior distribution of the unknown parameters. Due to the complexity of the resulting posterior distributions, Markov chain Monte Carlo algorithms are proposed for (sample-based) detection/estimation. On the other hand, to take full advantage of the sequential nature of the ECG, a dynamic model is proposed under a similar Bayesian framework. Sequential Monte Carlo methods (SMC) are also considered for delineation and waveform estimation. In the last part of the thesis, two Bayesian models introduced in this thesis are adapted to address a specific clinical research problem referred to as T wave alternans (TWA) detection. One of the proposed approaches has served as an efficient analysis tool in the Endocardial T wave Alternans Study (ETWAS) project in collaboration with St. Jude Medical, Inc and Toulouse Rangueil Hospital. This project was devoted to prospectively assess the feasibility of TWA detection in repolarisation on EGM stored in ICD memories.
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Nagappa, Sharad. "Time-varying frequency analysis of bat echolocation signals using Monte Carlo methods." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4622.

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Echolocation in bats is a subject that has received much attention over the last few decades. Bat echolocation calls have evolved over millions of years and can be regarded as well suited to the task of active target-detection. In analysing the time-frequency structure of bat calls, it is hoped that some insight can be gained into their capabilities and limitations. Most analysis of calls is performed using non-parametric techniques such as the short time Fourier transform. The resulting time-frequency distributions are often ambiguous, leading to further uncertainty in any subsequent analysis which depends on the time-frequency distribution. There is thus a need to develop a method which allows improved time-frequency characterisation of bat echolocation calls. The aim of this work is to develop a parametric approach for signal analysis, specifically taking into account the varied nature of bat echolocation calls in the signal model. A time-varying harmonic signal model with a polynomial chirp basis is used to track the instantaneous frequency components of the signal. The model is placed within a Bayesian context and a particle filter is used to implement the filter. Marginalisation of parameters is considered, leading to the development of a new marginalised particle filter (MPF) which is used to implement the algorithm. Efficient reversible jump moves are formulated for estimation of the unknown (and varying) number of frequency components and higher harmonics. The algorithm is applied to the analysis of synthetic signals and the performance is compared with an existing algorithm in the literature which relies on the Rao-Blackwellised particle filter (RBPF) for online state estimation and a jump Markov system for estimation of the unknown number of harmonic components. A comparison of the relative complexity of the RBPF and the MPF is presented. Additionally, it is shown that the MPF-based algorithm performs no worse than the RBPF, and in some cases, better, for the test signals considered. Comparisons are also presented from various reversible jump sampling schemes for estimation of the time-varying number of tones and harmonics. The algorithm is subsequently applied to the analysis of bat echolocation calls to establish the improvements obtained from the new algorithm. The calls considered are both amplitude and frequency modulated and are of varying durations. The calls are analysed using polynomial basis functions of different orders and the performance of these basis functions is compared. Inharmonicity, which is deviation of overtones away from integer multiples of the fundamental frequency, is examined in echolocation calls from several bat species. The results conclude with an application of the algorithm to the analysis of calls from the feeding buzz, a sequence of extremely short duration calls emitted at high pulse repetition frequency, where it is shown that reasonable time-frequency characterisation can be achieved for these calls.
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Ramnarain, Pallavi. "A Comparative Analysis of Methods for Baseline Drift Removal in Preterm Infant Respiration Signals." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/138.

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Breathing is a vital function intrinsic to the survival of any human being. In preterm infants it is an important indicator of maturation and feeding competency, which is a hallmark for hospital release. The recommended method of measurement of infant respiration is the use of thermistors. Accurate event detection within thermistor generated signals relies heavily upon effective noise reduction, specifically baseline drift removal. Baseline drift originates from several sensor-based factors, including thermistor placement within the sensor and in relation to the infant nares. This work compares four methods for baseline drift removal using the same event detection algorithm. The methods compared were a linear spline subtraction, a cubic spline subtraction, a neural network baseline approximation, and a double differentiation of the thermistor signal. The method yielding the highest event detection rate was shown to be the double differentiation method, which serves to attenuate the baseline drift to zero without approximating and subtracting it.
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Fuchs, Karen [Verfasser], and Gerhard [Akademischer Betreuer] Tutz. "Functional data analysis methods for the evaluation of sensor signals / Karen Fuchs ; Betreuer: Gerhard Tutz." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2017. http://d-nb.info/1156533767/34.

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Vaerenbergh, Steven Van. "Kernel Methods for Nonlinear Identification, Equalization and Separation of Signals." Doctoral thesis, Universidad de Cantabria, 2010. http://hdl.handle.net/10803/10673.

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En la última década, los métodos kernel (métodos núcleo) han demostrado ser técnicas muy eficaces en la resolución de problemas no lineales. Parte de su éxito puede atribuirse a su sólida base matemática dentro de los espacios de Hilbert generados por funciones kernel ("reproducing kernel Hilbert spaces", RKHS); y al hecho de que resultan en problemas convexos de optimización. Además, son aproximadores universales y la complejidad computacional que requieren es moderada. Gracias a estas características, los métodos kernel constituyen una alternativa atractiva a las técnicas tradicionales no lineales, como las series de Volterra, los polinómios y las redes neuronales. Los métodos kernel también presentan ciertos inconvenientes que deben ser abordados adecuadamente en las distintas aplicaciones, por ejemplo, las dificultades asociadas al manejo de grandes conjuntos de datos y los problemas de sobreajuste ocasionados al trabajar en espacios de dimensionalidad infinita.En este trabajo se desarrolla un conjunto de algoritmos basados en métodos kernel para resolver una serie de problemas no lineales, dentro del ámbito del procesado de señal y las comunicaciones. En particular, se tratan problemas de identificación e igualación de sistemas no lineales, y problemas de separación ciega de fuentes no lineal ("blind source separation", BSS). Esta tesis se divide en tres partes. La primera parte consiste en un estudio de la literatura sobre los métodos kernel. En la segunda parte, se proponen una serie de técnicas nuevas basadas en regresión con kernels para resolver problemas de identificación e igualación de sistemas de Wiener y de Hammerstein, en casos supervisados y ciegos. Como contribución adicional se estudia el campo del filtrado adaptativo mediante kernels y se proponen dos algoritmos recursivos de mínimos cuadrados mediante kernels ("kernel recursive least-squares", KRLS). En la tercera parte se tratan problemas de decodificación ciega en que las fuentes son dispersas, como es el caso en comunicaciones digitales. La dispersidad de las fuentes se refleja en que las muestras observadas se agrupan, lo cual ha permitido diseñar técnicas de decodificación basadas en agrupamiento espectral. Las técnicas propuestas se han aplicado al problema de la decodificación ciega de canales MIMO rápidamente variantes en el tiempo, y a la separación ciega de fuentes post no lineal.
In the last decade, kernel methods have become established techniques to perform nonlinear signal processing. Thanks to their foundation in the solid mathematical framework of reproducing kernel Hilbert spaces (RKHS), kernel methods yield convex optimization problems. In addition, they are universal nonlinear approximators and require only moderate computational complexity. These properties make them an attractive alternative to traditional nonlinear techniques such as Volterra series, polynomial filters and neural networks.This work aims to study the application of kernel methods to resolve nonlinear problems in signal processing and communications. Specifically, the problems treated in this thesis consist of the identification and equalization of nonlinear systems, both in supervised and blind scenarios, kernel adaptive filtering and nonlinear blind source separation.In a first contribution, a framework for identification and equalization of nonlinear Wiener and Hammerstein systems is designed, based on kernel canonical correlation analysis (KCCA). As a result of this study, various other related techniques are proposed, including two kernel recursive least squares (KRLS) algorithms with fixed memory size, and a KCCA-based blind equalization technique for Wiener systems that uses oversampling. The second part of this thesis treats two nonlinear blind decoding problems of sparse data, posed under conditions that do not permit the application of traditional clustering techniques. For these problems, which include the blind decoding of fast time-varying MIMO channels, a set of algorithms based on spectral clustering is designed. The effectiveness of the proposed techniques is demonstrated through various simulations.
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Anand, K. "Methods for Blind Separation of Co-Channel BPSK Signals Arriving at an Antenna Array and Their Performance Analysis." Thesis, Indian Institute of Science, 1995. http://hdl.handle.net/2005/123.

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Capacity improvement of Wireless Communication Systems is a very important area of current research. The goal is to increase the number of users supported by the system per unit bandwidth allotted. One important way of achieving this improvement is to use multiple antennas backed by intelligent signal processing. In this thesis, we present methods for blind separation of co-channel BPSK signals arriving at an antenna array. These methods consist of two parts, Constellation Estimation and Assignment. We give two methods for constellation estimation, the Smallest Distance Clustering and the Maximum Likelihood Estimation. While the latter is theoretically sound,the former is Computationally simple and intuitively appealing. We show that the Maximum Likelihood Constellation Estimation is well approximated by the Smallest Distance Clustering Algorithm at high SNR. The Assignment Algorithm exploits the structure of the BPSK signals. We observe that both the methods for estimating the constellation vectors perform very well at high SNR and nearly attain Cramer-Rao bounds. Using this fact and noting that the Assignment Algorithm causes negligble error at high SNR, we derive an upper bound on the probability of bit error for the above methods at high SNR. This upper bound falls very rapidly with increasing SNR, showing that our constellation estimation-assignment approach is very efficient. Simulation results are given to demonstrate the usefulness of the bounds.
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Baccherini, Simona. "Pattern recognition methods for EMG prosthetic control." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/12033/.

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In this work we focus on pattern recognition methods related to EMG upper-limb prosthetic control. After giving a detailed review of the most widely used classification methods, we propose a new classification approach. It comes as a result of comparison in the Fourier analysis between able-bodied and trans-radial amputee subjects. We thus suggest a different classification method which considers each surface electrodes contribute separately, together with five time domain features, obtaining an average classification accuracy equals to 75% on a sample of trans-radial amputees. We propose an automatic feature selection procedure as a minimization problem in order to improve the method and its robustness.
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Books on the topic "Signals’ analysis methods"

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Signals and systems: Analysis using transform methods and MATLAB. Boston: McGraw-Hill, Higher Education, 2004.

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Signals and systems: Analysis using transform methods and MATLAB. 2nd ed. New York: McGraw-Hill, 2012.

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Leonowicz, Zbigniew. Parametric methods for time-frequency analysis of electric signals. Wrocław: Oficyna Wydawnicza Politechniki Wrocławskiej, 2006.

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An introduction to the digital analysis of stationary signals. Bristol, England: A. Hilger, 1989.

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Li, Jian, Ph. D., 1965- and Stoica Petre, eds. Spectral analysis of signals: The missing data case. [San Rafael, Calif.]: Morgan & Claypool Publishers, 2005.

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Signals and systems analysis in biomedical engineering. 2nd ed. Boca Raton: Taylor & Francis Group, 2010.

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1968-, Ling Tonghua, and Zhang Yiping 1970-, eds. Bao po zhen dong xin hao fen xi li lun yu ji shu: Analysis of blast vibration singals-theories and methods. Beijing: Ke xue chu ban she, 2009.

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Manfredi, Claudia, ed. Models and Analysis of Vocal Emissions for Biomedical Applications. Florence: Firenze University Press, 2013. http://dx.doi.org/10.36253/978-88-6655-470-7.

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The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies.
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Manfredi, Claudia, ed. Models and Analysis of Vocal Emissions for Biomedical Applications. Florence: Firenze University Press, 2009. http://dx.doi.org/10.36253/978-88-6453-096-3.

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The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies.
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Manfredi, Claudia, ed. Models and Analysis of Vocal Emissions for Biomedical Applications. Florence: Firenze University Press, 2011. http://dx.doi.org/10.36253/978-88-6655-011-2.

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The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies.
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Book chapters on the topic "Signals’ analysis methods"

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Kiasaleh, Kamran. "Signal Processing Methods for Biological Signals." In Biological Signals Classification and Analysis, 175–275. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-54879-6_4.

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Kiasaleh, Kamran. "Signal Decomposition Methods." In Biological Signals Classification and Analysis, 277–376. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-54879-6_5.

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Wu, Xiaohui, Guoli Ji, and Qingshun Quinn Li. "Computational Analysis of Plant Polyadenylation Signals." In Methods in Molecular Biology, 3–11. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-2175-1_1.

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von Heijne, Gunnar. "Cleavage-Sites in Protein Targeting Signals." In Methods in Protein Sequence Analysis, 231–38. Basel: Birkhäuser Basel, 1991. http://dx.doi.org/10.1007/978-3-0348-5678-2_23.

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Schmal, Christoph, Gregor Mönke, and Adrián E. Granada. "Analysis of Complex Circadian Time Series Data Using Wavelets." In Methods in Molecular Biology, 35–54. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2249-0_3.

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AbstractExperiments that compare rhythmic properties across different genetic alterations and entrainment conditions underlie some of the most important breakthroughs in circadian biology. A robust estimation of the rhythmic properties of the circadian signals goes hand in hand with these discoveries. Widely applied traditional signal analysis methods such as fitting cosine functions or Fourier transformations rely on the assumption that oscillation periods do not change over time. However, novel high-resolution recording techniques have shown that, most commonly, circadian signals exhibit time-dependent changes of periods and amplitudes which cannot be captured with the traditional approaches. In this chapter we introduce a method to determine time-dependent properties of oscillatory signals, using the novel open-source Python-based Biological Oscillations Analysis Toolkit (pyBOAT). We show with examples how to detect rhythms, compute and interpret high-resolution time-dependent spectral results, analyze the main oscillatory component, and to subsequently determine these main components’ time-dependent instantaneous period, amplitude, and phase. We introduce step-by-step how such an analysis can be done by means of the easy-to-use point-and-click graphical user interface (GUI) provided by pyBOAT or executed within a Python programming environment. Concepts are explained using simulated signals as well as experimentally obtained time series.
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Zhangy, L. Q., and A. Cichockiz. "Independent Residual Analysis for Temporally Correlated Signals." In Computational Methods in Neural Modeling, 158–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44868-3_21.

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Sergienko, Vladimir P., and Sergey N. Bukharov. "Methods of Analysis of Noise and Vibration Signals." In Noise and Vibration in Friction Systems, 57–81. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11334-0_4.

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Isermann, Rolf, and Marco Münchhof. "Spectral Analysis Methods for Periodic and Non-Periodic Signals." In Identification of Dynamic Systems, 77–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-78879-9_3.

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Yan, Tao, Ying Wang, Bo Qu, Xiao Liu, and Guoyong Wang. "Analysis Methods of Linear Distortion Characteristics for GNSS Signals." In Lecture Notes in Electrical Engineering, 183–95. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0029-5_17.

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Akiyama, Hiroki, and Hiroyuki Kamiguchi. "Analysis of Calcium Signals in Steering Neuronal Growth Cones In Vitro." In Methods in Molecular Biology, 17–27. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0777-9_2.

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Conference papers on the topic "Signals’ analysis methods"

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Luzhansky, Edward, Fow-Sen Choa, Scott Merritt, Anthony Yu, and Michael Krainak. "Comparative Analysis of QCL MWIR and SWIR Communication with PPM Signals." In Adaptive Optics: Analysis, Methods & Systems. Washington, D.C.: OSA, 2015. http://dx.doi.org/10.1364/aoms.2015.jt5a.7.

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Gladysz, Szymon, and Erez N. Ribak. "Recovery of Exoplanetary Signals in Re-dispersed Speckle Clutter." In Adaptive Optics: Methods, Analysis and Applications. Washington, D.C.: OSA, 2011. http://dx.doi.org/10.1364/aopt.2011.jwa10.

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Haufe, Daniel, Nektarios Koukourakis, Lars Büttner, and Jürgen W. Czarske. "Transmission of Multiple Independent Signals Through a Multimode Fiber Using Optical Wavefront Shaping." In Adaptive Optics: Analysis, Methods & Systems. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/aoms.2016.aoth1c.3.

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Meiri, Amihai, Carl G. Ebeling, Jason Martineau, Zeev Zalevsky, Jordan M. Gerton, and Rajesh Menon. "Self-Interference of Coherent and Incoherent Signals for Sub-Nanometer Localization of Single Emitters." In Adaptive Optics: Analysis, Methods & Systems. Washington, D.C.: OSA, 2015. http://dx.doi.org/10.1364/aoms.2015.jw3a.3.

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Oktem, Figen S., and Haldun M. Ozaktas. "Condition number in recovery of signals from partial fractional Fourier domain information." In Adaptive Optics: Methods, Analysis and Applications. Washington, D.C.: OSA, 2013. http://dx.doi.org/10.1364/aopt.2013.jtu4a.18.

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Ardeenawatie Awang, Saidatul, M. P. Paulraj, and Sazali Yaacob. "Analysis of EEG signals by eigenvector methods." In 2012 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES 2012). IEEE, 2012. http://dx.doi.org/10.1109/iecbes.2012.6498164.

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Kalbfleisch, Paul, Svenja Horn, and Monika Ivantysynova. "Cyclostationary Analysis of Measured Pump Acoustic and Vibration Signals." In BATH/ASME 2018 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/fpmc2018-8899.

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The stationary signal assumption is convenient as its signal processing methods are the minimum effort required to characterize periodic signals and therefore the most common. However, signals from rotating machines have been found to naturally be characterized as cyclostationary. The existent of natural phenomenon such as, shaft imbalances, turbulent fluid flows, friction, combustion forces, and torsional vibrations create modulation effects, that can be seen in the measured signals. These observed modulations in pump noise and vibration signals are synonymous to amplitude modulations (AM), frequency modulations (FM), and potentially phase modulations in electrical systems. Having this knowledge, the fluid power noise, vibration, and harshness (NVH) researchers can draw from an enormous amount of progress made in the modern telecommunication signal processing methods of cyclostationary signals. This article introduces the basic concepts of cyclostationary signals, some of their signal processing techniques, and a simple example of analysis for a positive displacement machine through the cyclostationary paradigm.
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Nam, Ki-Woo, Kun-Chan Lee, and Jeong-Hwan Oh. "Application of Joint-Time Frequency Analysis Methods for Nondestructive Evaluation." In ASME 1999 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/imece1999-0890.

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Abstract Application of signal processing techniques to nondestructive evaluation (NDE) in general and acoustic emission (AE) studies in particular has become a standard tool in determining the frequency characteristics of the signals and relating these characteristics to the integrity of the structure under consideration. Recent studies have shown that the frequency characteristics of ultrasonic signals from evolving damage during cyclic (fatigue) and dynamic loads change with time; in other words, the signals are nonstationary, and that these changes can be related to the nature of the damage taking place during loading. A joint time-frequency analysis such as Short Time Fourier Transform (STFT) and Wigner-Ville distribution (WVD), can in principle be used to determine the time dependent frequency characteristics of nonstationary signals in presence of background noise. In this study these techniques are applied to analyze AE signals from fatigue crack propagation in 5083 aluminum alloys and ultrasonic signals in degraded austenitic 316 stainless steels, to study the evolution of damage in these materials. It is demonstrated that the nonstationary characteristics of both AE and ultrasonic signals could be analyzed effectively by these methods. STFT was found to be more effective in analyzing AE signals, and WVD was more effective for analyzing the attenuation and frequency characteristics of degraded materials through ultrasonics. It is indicated that the time-frequency analysis methods should also be useful in evaluating crack propagation and final fracture process resulting from various damages and defects in structural members.
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Peneva Gospodinova, Evgeniya. "Hurst Methods for Fractal Analysis of Electrocardiographical Signals." In International Conference on Research in Engineering and Technology. ACAVENT, 2019. http://dx.doi.org/10.33422/researchconf.2019.12.895.

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Koch, Olivier. "Comparison of Multipactor Analysis Methods for Galileo Signals." In 2018 IEEE Conference on Antenna Measurements & Applications (CAMA). IEEE, 2018. http://dx.doi.org/10.1109/cama.2018.8530632.

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Reports on the topic "Signals’ analysis methods"

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Paulson, Albert S., and Gerald R. Swope. Signal Model Analysis Via Model-Critical Methods. Fort Belvoir, VA: Defense Technical Information Center, October 1988. http://dx.doi.org/10.21236/ada200685.

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Kumaresan, R. Parametric Time-Scale Methods in Signal Analysis. Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada274212.

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Bai, Z. D., and C. R. Rao. Spectral Analytic Methods for the Estimation of Number of Signals and Directions of Arrival. Fort Belvoir, VA: Defense Technical Information Center, November 1989. http://dx.doi.org/10.21236/ada217219.

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Simmons, Justin. Complete and Exact Small Signal Analysis of DC-to-DC Switched Power Converters Under Various Operating Modes and Control Methods. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.195.

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Corriveau, Elizabeth, Ashley Mossell, Holly VerMeulen, Samuel Beal, and Jay Clausen. The effectiveness of laser-induced breakdown spectroscopy (LIBS) as a quantitative tool for environmental characterization. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40263.

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Laser-induced breakdown spectroscopy (LIBS) is a rapid, low-cost analytical method with potential applications for quantitative analysis of soils for heavy metal contaminants found in military ranges. The Department of Defense (DoD), Army, and Department of Homeland Security (DHS) have mission requirements to acquire the ability to detect and identify chemicals of concern in the field. The quantitative potential of a commercial off-the-shelf (COTS) hand-held LIBS device and a classic laboratory bench-top LIBS system was examined by measuring heavy metals (antimony, tungsten, iron, lead, and zinc) in soils from six military ranges. To ensure the accuracy of the quantified results, we also examined the soil samples using other hand-held and bench-top analytical methods, to include Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and X-Ray Fluorescence (XRF). The effects of soil heterogeneity on quantitative analysis were reviewed with hand-held and bench-top systems and compared multivariate and univariate calibration algorithms for heavy metal quantification. In addition, the influence of cold temperatures on signal intensity and resulting concentration were examined to further assess the viability of this technology in cold environments. Overall, the results indicate that additional work should be performed to enhance the ability of LIBS as a reliable quantitative analytical tool.
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Ripey, Mariya. NUMBERS IN THE NEWS TEXT (BASED ON MATERIAL OF ONE ISSUE OF NATIONWIDE NEWSPAPER “DAY”). Ivan Franko National University of Lviv, March 2021. http://dx.doi.org/10.30970/vjo.2021.50.11106.

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The article is devoted to the analysis of the digital content of publications of one issue of the daily All-Ukrainian newspaper “Den” (March 13-14, 2020). The author aims to identify the main thematic groups of digital designations, as well as to consider cases of justified and unsuccessful use of digital designations. Applying the content analysis method, the author identifies publications that contain numerical notations, determines the number of such notations and their affiliation with the main subject groups. Finds that the thematic group of digital designations “time” (58.6% of all digital designations) is much more dominant. This indicates that timing is the most important task of a newspaper text. The second largest group of digital designations is “measure” (15.8% of all digital designations). It covers dimensions and proportions, measurements of distance, weight, volume, and more. The third largest group of digital signage is money (8.2% of all digital signage), the fourth is numbering (5.2% of all digital signage), and the fifth is people (4.4% of all digital signage). The author focuses on the fact that the digits of the journalist’s text are both a source of information and a catch for the reader. Vivid indicators give the text a sense of accuracy. When referring digital data to the text, journalists must adhere to certain rules for the writing of ordinal numbers with incremental graduation; submission of dates; pointing to unique integers that are combined (or not combined) with units of physical quantities, monetary units, etc.; writing a numerator at the beginning of a sentence; unified presentation of data. This will greatly facilitate the reader’s perception of the information.
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Jury, William A., and David Russo. Characterization of Field-Scale Solute Transport in Spatially Variable Unsaturated Field Soils. United States Department of Agriculture, January 1994. http://dx.doi.org/10.32747/1994.7568772.bard.

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This report describes activity conducted in several lines of research associated with field-scale water and solute processes. A major effort was put forth developing a stochastic continuum analysis for an important class of problems involving flow of reactive and non reactive chemicals under steady unsaturated flow. The field-scale velocity covariance tensor has been derived from local soil properties and their variability, producing a large-scale description of the medium that embodies all of the local variability in a statistical sense. Special cases of anisotropic medium properties not aligned along the flow direction of spatially variable solute sorption were analysed in detail, revealing a dependence of solute spreading on subtle features of the variability of the medium, such as cross-correlations between sorption and conductivity. A novel method was developed and tested for measuring hydraulic conductivity at the scale of observation through the interpretation of a solute transport outflow curve as a stochastic-convective process. This undertaking provided a host of new K(q) relationships for existing solute experiments and also laid the foundation for future work developing a self-consistent description of flow and transport under these conditions. Numerical codes were developed for calculating K(q) functions for a variety of solute pulse outflow shapes, including lognormal, Fickian, Mobile-Immobile water, and bimodal. Testing of this new approach against conventional methodology was mixed, and agreed most closely when the assumptions of the new method were met. We conclude that this procedure offers a valuable alternative to conventional methods of measuring K(q), particularly when the application of the method is at a scale (e.g. and agricultural field) that is large compared to the common scale at which conventional K(q) devices operate. The same problem was approached from a numerical perspective, by studying the feasibility of inverting a solute outflow signal to yield the hydraulic parameters of the medium that housed the experiment. We found that the inverse problem was solvable under certain conditions, depending on the amount of noise in the signal and the degree of heterogeneity in the medium. A realistic three dimensional model of transient water and solute movement in a heterogeneous medium that contains plant roots was developed and tested. The approach taken was to generate a single realization of this complex flow event, and examine the results to see whether features were present that might be overlooked in less sophisticated model efforts. One such feature revealed is transverse dispersion, which is a critically important component in the development of macrodispersion in the longitudinal direction. The lateral mixing that was observed greatly exceeded that predicted from simpler approaches, suggesting that at least part of the important physics of the mixing process is embedded in the complexity of three dimensional flow. Another important finding was the observation that variability can produce a pseudo-kinetic behavior for solute adsorption, even when the local models used are equilibrium.
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Baron, Lisa. Post-Dorian shoreline change at Cape Hatteras National Seashore: 2019 report. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2282127.

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In 2018 and 2019 the Southeast Coast Network (SECN), with assistance from park staff, collected long-term shoreline monitoring data at Cape Hatteras National Seashore as part of the National Park Service (NPS) Vital Signs Monitoring Program. Monitoring was conducted following methods developed by the NPS Northeast Coastal and Barrier Network and consisted of mapping the high-tide swash line using a Global Positioning System unit in the spring of each year (Psuty et al. 2010). Shoreline change was calculated using the Digital Shoreline Analysis System (DSAS) developed by the United States Geological Survey (USGS; Himmelstoss et al. 2018). Following the same field methods used for monitoring long-term shoreline change, geospatial data were collected as part of the Hurricane Dorian (or Dorian) Incident Response from September 12–16, 2019. This report summarizes the post-Dorian data and the previous two shoreline data collection efforts (spring 2019 and fall 2018).
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Ron, Eliora, and Eugene Eugene Nester. Global functional genomics of plant cell transformation by agrobacterium. United States Department of Agriculture, March 2009. http://dx.doi.org/10.32747/2009.7695860.bard.

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The aim of this study was to carry out a global functional genomics analysis of plant cell transformation by Agrobacterium in order to define and characterize the physiology of Agrobacterium in the acidic environment of a wounded plant. We planed to study the proteome and transcriptome of Agrobacterium in response to a change in pH, from 7.2 to 5.5 and identify genes and circuits directly involved in this change. Bacteria-plant interactions involve a large number of global regulatory systems, which are essential for protection against new stressful conditions. The interaction of bacteria with their hosts has been previously studied by genetic-physiological methods. We wanted to make use of the new capabilities to study these interactions on a global scale, using transcription analysis (transcriptomics, microarrays) and proteomics (2D gel electrophoresis and mass spectrometry). The results provided extensive data on the functional genomics under conditions that partially mimic plant infection and – in addition - revealed some surprising and significant data. Thus, we identified the genes whose expression is modulated when Agrobacterium is grown under the acidic conditions found in the rhizosphere (pH 5.5), an essential environmental factor in Agrobacterium – plant interactions essential for induction of the virulence program by plant signal molecules. Among the 45 genes whose expression was significantly elevated, of special interest is the two-component chromosomally encoded system, ChvG/I which is involved in regulating acid inducible genes. A second exciting system under acid and ChvG/Icontrol is a secretion system for proteins, T6SS, encoded by 14 genes which appears to be important for Rhizobium leguminosarum nodule formation and nitrogen fixation and for virulence of Agrobacterium. The proteome analysis revealed that gamma aminobutyric acid (GABA), a metabolite secreted by wounded plants, induces the synthesis of an Agrobacterium lactonase which degrades the quorum sensing signal, N-acyl homoserine lactone (AHL), resulting in attenuation of virulence. In addition, through a transcriptomic analysis of Agrobacterium growing at the pH of the rhizosphere (pH=5.5), we demonstrated that salicylic acid (SA) a well-studied plant signal molecule important in plant defense, attenuates Agrobacterium virulence in two distinct ways - by down regulating the synthesis of the virulence (vir) genes required for the processing and transfer of the T-DNA and by inducing the same lactonase, which in turn degrades the AHL. Thus, GABA and SA with different molecular structures, induce the expression of these same genes. The identification of genes whose expression is modulated by conditions that mimic plant infection, as well as the identification of regulatory molecules that help control the early stages of infection, advance our understanding of this complex bacterial-plant interaction and has immediate potential applications to modify it. We expect that the data generated by our research will be used to develop novel strategies for the control of crown gall disease. Moreover, these results will also provide the basis for future biotechnological approaches that will use genetic manipulations to improve bacterial-plant interactions, leading to more efficient DNA transfer to recalcitrant plants and robust symbiosis. These advances will, in turn, contribute to plant protection by introducing genes for resistance against other bacteria, pests and environmental stress.
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Fluhr, Robert, and Maor Bar-Peled. Novel Lectin Controls Wound-responses in Arabidopsis. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7697123.bard.

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Innate immune responses in animals and plants involve receptors that recognize microbe-associated molecules. In plants, one set of this defense system is characterized by large families of TIR–nucleotide binding site–leucine-rich repeat (TIR-NBS-LRR) resistance genes. The direct interaction between plant proteins harboring the TIR domain with proteins that transmit and facilitate a signaling pathway has yet to be shown. The Arabidopsis genome encodes TIR-domain containing genes that lack NBS and LRR whose functions are unknown. Here we investigated the functional role of such protein, TLW1 (TIR LECTIN WOUNDRESPONSIVE1). The TLW1 gene encodes a protein with two domains: a TIR domain linked to a lectin-containing domain. Our specific aim in this proposal was to examine the ramifications of the TL1-glycan interaction by; A) The functional characterization of TL1 activity in the context of plant wound response and B) Examine the hypothesis that wounding induced specific polysaccharides and examine them as candidates for TL-1 interactive glycan compounds. The Weizmann group showed TLW1 transcripts are rapidly induced by wounding in a JA-independent pathway and T-DNA-tagged tlw1 mutants that lack TLW1 transcripts, fail to initiate the full systemic wound response. Transcriptome methodology analysis was set up and transcriptome analyses indicates a two-fold reduced level of JA-responsive but not JA-independent transcripts. The TIR domain of TLW1 was found to interact directly with the KAT2/PED1 gene product responsible for the final b-oxidation steps in peroxisomal-basedJA biosynthesis. To identify potential binding target(s) of TL1 in plant wound response, the CCRC group first expressed recombinant TL1 in bacterial cells and optimized conditions for the protein expression. TL1 was most highly expressed in ArcticExpress cell line. Different types of extraction buffers and extraction methods were used to prepare plant extracts for TL1 binding assay. Optimized condition for glycan labeling was determined, and 2-aminobenzamide was used to label plant extracts. Sensitivity of MALDI and LC-MS using standard glycans. THAP (2,4,6- Trihydroxyacetophenone) showed minimal background peaks at positive mode of MALDI, however, it was insensitive with a minimum detection level of 100 ng. Using LC-MS, sensitivity was highly increased enough to detect 30 pmol concentration. However, patterns of total glycans displayed no significant difference between different extraction conditions when samples were separated with Dionex ICS-2000 ion chromatography system. Transgenic plants over-expressing lectin domains were generated to obtain active lectin domain in plant cells. Insertion of the overexpression construct into the plant genome was confirmed by antibiotic selection and genomic DNA PCR. However, RT-PCR analysis was not able to detect increased level of the transcripts. Binding ability of azelaic acid to recombinant TL1. Azelaic acid was detected in GST-TL1 elution fraction, however, DHB matrix has the same mass in background signals, which needs to be further tested on other matrices. The major findings showed the importance of TLW1 in regulating wound response. The findings demonstrate completely novel and unexpected TIR domain interactions and reveal a control nexus and mechanism that contributes to the propagation of wound responses in Arabidopsis. The implications are to our understanding of the function of TIR domains and to the notion that early molecular events occur systemically within minutes of a plant sustaining a wound. A WEB site (http://genome.weizmann.ac.il/hormonometer/) was set up that enables scientists to interact with a collated plant hormone database.
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