Relevant bibliographies by topics / Frequency estimator

Academic literature on the topic 'Frequency estimator'

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Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Frequency estimator"

1

Zhou, Shen, and Liu Rongfang. "Efficient and Accurate Frequency Estimator under Low SNR by Phase Unwrapping." Mathematical Problems in Engineering 2019 (April 14, 2019): 1–6. http://dx.doi.org/10.1155/2019/7396074.

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In the case of low signal-to-noise ratio, for the frequency estimation of single-frequency sinusoidal signals with additive white Gaussian noise, the phase unwrapping estimator usually performs poorly. In this paper, an efficient and accurate method is proposed to address this problem. Different from other methods, based on fast Fourier transform, the sampled signals are estimated with the variances approaching the Cramer-Rao bound, followed with the maximum likelihood estimation of the frequency. Experimental results reveal that our estimator has a better performance than other phase unwrapping estimators. Compared with the state-of-the-art method, our estimator has the same accuracy and lower computational complexity. Besides, our estimator does not have the estimation bias.
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Zhu, Dong Xu, Jiu Ying Zhi, and Gang Fu. "A New Frequency Estimator in Multi-Frequency Estimation." Applied Mechanics and Materials 602-605 (August 2014): 3727–30. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.3727.

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By analyzing the second-order and fourth-order IIR filter that affect the variance adaptive prove second-order IIR model has a single peak characteristics, to achieve stable convergence; while the higher-order IIR model polymorphic, so the need for the estimated parameters are initialized conclusions. Proposed use of FFT frequency estimation assisted IIR adaptive filter to achieve more frequent rate estimation, parameter estimation for the multi-point frequencies adaptive selection process provides a theoretical basis.
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Kuc, Roman, and Hilda Li. "Reduced-Order Autoregressive Modeling for Center-Frequency Estimation." Ultrasonic Imaging 7, no. 3 (July 1985): 244–51. http://dx.doi.org/10.1177/016173468500700304.

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The center frequency of a narrowband, discrete-time random process, such as a reflected ultrasound signal, is estimated from the parameter values of a reduced, second-order autoregressive (AR) model. This approach is proposed as a fast estimator that performs better than the zero-crossing count estimate for determining the center-frequency location. The parameter values are obtained through a linear prediction analysis on the correlated random process, which in this case is identical to the maximum entropy method for spectral estimation. The frequency of the maximum of the second-order model spectrum is determined from these parameters and is used as the center-frequency estimate. This estimate can be computed very efficiently, requiring only the estimates of the first three terms of the process autocorrelation function. The bias and variance properties of this estimator are determined for a random process having a Gaussian-shaped spectrum and compared to those of the ideal FM frequency discriminator, zero-crossing count estimator and a correlation estimator. It is found that the variance values for the reduced-order AR model center-frequency estimator lie between those for the ideal FM frequency discriminator and the zero-crossing count estimator.
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Zhu, Dong Xu, Jiu Ying Zhi, and Gang Fu. "Study on IIR Adaptive Frequency Estimator in the Multi-Frequency Estimation." Applied Mechanics and Materials 602-605 (August 2014): 3731–34. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.3731.

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Propose a use of IIR adaptive frequency estimator to achieve multi-frequency estimation algorithm. Analysis IIR filter characteristics, indicating that the second-order IIR model has a single peak characteristics, to achieve stable convergence; while the higher-order IIR model polymorphic, so the need for the estimated parameters are initialized. More traditional phase locked loop algorithm, which has no mixing components, to achieve the advantages of full-band frequency estimation, frequency estimation accuracy under the same environment and phase locked loop fairly.
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Kou, Ming Xin, Jian Hua Lin, and Gang Fu. "Multi-Frequency Estimates Based on IIR Adaptive Frequency Estimator." Advanced Materials Research 989-994 (July 2014): 3985–88. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.3985.

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Presents a IIR adaptive frequency estimator to achieve multi-frequency estimation algorithm. More traditional phase locked loop algorithm, which has no mixing components, to achieve the advantages of full-band frequency estimation, frequency estimation accuracy under the same environment and phase locked loop fairly.
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Zhang, Gangbing, Lu Jin, and Defeng (David) Huang. "A dichotomous search-based frequency estimator with generic analytical expression." Modern Physics Letters B 32, no. 34n36 (December 30, 2018): 1840095. http://dx.doi.org/10.1142/s021798491840095x.

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Fine resolution frequency estimation of a single-tone complex sinusoidal signal in the additive white Gaussian noise is of importance in many fields. In this paper, a generic analytical expression is proposed to refine the residual of a dichotomous search, leading to an estimator with much less iterations than the conventional dichotomous search estimator. Compared with other existing estimators, the proposed estimator has a better trade-off between performance and computational complexity. Simulation results demonstrate that the root-mean-square error (RMSE) of the proposed estimator is closer to the Cramer–Rao lower bound (CRLB) than other estimators over the whole frequency interval when the signal-to-noise ratio (SNR) is above a threshold.
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Herment, A., and J. F. Giovannelli. "An Adaptive Approach to Computing the Spectrum and Mean Frequency of Doppler Signals." Ultrasonic Imaging 17, no. 1 (January 1995): 1–26. http://dx.doi.org/10.1177/016173469501700101.

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Modern ultrasound Doppler systems are facing the problem of processing increasingly shorter data sets. Spectral analysis of the strongly nonstationary Doppler signal needs to shorten the analysis window while maintaining a low variance and high resolution spectrum. Color flow imaging requires estimation of the Doppler mean frequency from even shorter Doppler data sets to obtain both a high frame rate and high spatial resolution. We reconsider these two estimation problems in light of adaptive methods. A regularized parametric method for spectral analysis as well as an adapted mean frequency estimator are developed. The choice of the adaptive criterion is then addressed and adaptive spectral and mean frequency estimators are developed to minimize the mean square error on estimation in the presence of noise. Two suboptimal spectral and mean-frequency estimators are then derived for real-time applications. Finally, their performance is compared to that of both the FFT based periodogram and the AR parametric spectral analysis for the spectral estimator, and, to both the correlation angle and the Kristoffersen's [8] estimators for the mean frequency estimator using Doppler data recorded in vitro.
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Millar, Russell B. "A better estimator of mortality rate from age-frequency data." Canadian Journal of Fisheries and Aquatic Sciences 72, no. 3 (March 2015): 364–75. http://dx.doi.org/10.1139/cjfas-2014-0193.

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The Chapman–Robson and weighted-regression estimators are currently the two preferred methods for estimation of instantaneous mortality, z, from a cross-sectional sample of age-frequency data. They are derived under the assumption of steady-state population dynamics. Here, a new estimator is developed from a population model that explicitly includes annual variability in recruitment. The new estimator is trivial to implement using existing generalized linear mixed model software. It is vastly superior to both the Chapman–Robson and weighted-regression estimators under a wide range of simulation scenarios in which sources of variability include partial recruitment to the fishery, autocorrelated annual recruitment, variability in annual survival, ageing error, and sampling randomness. All estimators produced confidence intervals that had lower actual coverage than their nominal 95% coverage. Nonetheless, the new estimator had the highest actual coverage, and under some scenarios this was achieved with a narrowest confidence interval.
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Saber, Mohamed, and El-sayed M.El-Kenawy. "Design and implementation of accurate frequency estimator depend on deep learning." International Journal of Engineering & Technology 9, no. 2 (April 3, 2020): 367. http://dx.doi.org/10.14419/ijet.v9i2.30473.

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An Accurate, efficient, and stable system to estimate the unknown input frequency of a sinusoidal signal is presented. The proposed design solves the main drawback of the existing phase-based estimator which called a derivative estimator depend on deep learning. These limitations are the inability to estimate low frequencies and the large estimation errors for the frequencies near the Nyquist rate. A Brief mathematical analysis in discrete-time of the proposed system is presented. Proposed estimator performance when the input is a single sinusoid, multiple sinusoids in the presence of additive white Gaussian noise (AWGN) are provided. The accuracy of the proposed esti-mator is the result of dividing the dynamic range of estimation to three regions (low frequencies, middle frequencies, high frequencies) and specify a different formula to calculate the estimated frequency in each region. The boundaries of each region are determined by using a Grey wolf optimizer (GWO) which training bidirectional recurrent neural networks (BRNN) to select the best weights for the estimated frequency. The simulation results ensure the accuracy and validity of the proposed estimator compared to the traditional one. The hardware implementation of enhanced estimator using field-programmable gate array (FPGA), consumed 265 mW, and worked at 375 MHz.
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Quinn, B. G. "On Kay's Frequency Estimator." Journal of Time Series Analysis 21, no. 6 (November 2000): 707–12. http://dx.doi.org/10.1111/1467-9892.00205.

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Dissertations / Theses on the topic "Frequency estimator"

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Palmer, Joseph. "A HIGH-ACCURACY AND LOW-COMPLEXITY CARRIER-OFFSET-FREQUENCY ESTIMATOR." International Foundation for Telemetering, 2007. http://hdl.handle.net/10150/604513.

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ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada
A single-tone frequency estimator for a non-uniformly sampled sinusoid is proposed. A nonuniformly sampled sinusoid may be generated from the received training sequences of a telemetry link. The frequency of the sinusoid matches the carrier-frequency-offset (CFO) of the received signal, and estimation of this quantity allows a receiver to compensate for the CFO. The performance bounds of this type of estimator have been investigated in the literature, though little work has been published on practical algorithms. The estimator proposed in this paper is a generalization of phase-increment estimators previously described in the literature. It exhibits a low computational complexity yet converges to theoretical bounds at high SNR. The paper argues that a periodic training sequence structure, combined with the new estimator, allows for a high-accuracy and lowcomplexity CFO compensator.
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Feldman, Jonathan Michael S. M. Massachusetts Institute of Technology. "The Augmented Geometrically Spaced Transform : applications of the single channel frequency estimator." Thesis, Massachusetts Institute of Technology, 2021. https://hdl.handle.net/1721.1/131006.

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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February, 2021
Cataloged from the official PDF version of thesis.
Includes bibliographical references (pages 99-103).
The Augmented Geometrically Spaced Transform (AGST) is an auditory model that is based on an inversion of the acoustic piano, where the piano produces music and the transform analyses it. In contrast with the standard spectrogram, which is a complex frequency vector versus time, the AGST is based around a matrix of frequencies, known as the AGST Frequency Matrix, where for every frequency in the matrix, a spectral envelope is computed using a Single Channel Frequency Estimator (SCFE). The core invention of the thesis is the algorithm for the SCFE, which computes spectral envelopes with maximally high definition in a computationally efficient manner. A bank of SCFEs is assembled into a constant Q transform, known as a Geometrically Spaced Transform (GST). The GST can be used to visualize harmonics inside of musical notes, or audio in general, in a constant Q fashion. It is then shown that the AGST is a good front-end model for computational pitch perception. For example, it can be used to solve an important problem in auditory perception, the case of the missing fundamental. The entire thesis is framed in the context of building artificially intelligent music systems, including synthetic listeners (machines that listen in the way that people do), and synthetic performers (machines that allow for interactive music performance).
by Jonathan Michael Feldman.
S.M.
S.M. Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences
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3

Kitchen, John. "The effect of quadrature hybrid errors on a phase difference frequency estimator and methods for correction /." Title page, contents and summary only, 1991. http://web4.library.adelaide.edu.au/theses/09AS/09ask62.pdf.

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Cobb, Richard E. "Confidence bands, measurement noise, and multiple input - multiple output measurements using three-channel frequency response function estimator." Diss., Virginia Polytechnic Institute and State University, 1988. http://hdl.handle.net/10919/53675.

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A three-channel Frequency Response Function (FRF) estimator is discussed and statistical relations developed. Methods for estimating the variance of the FRF magnitude and levels of uncorrelated content in the test signals are developed. FRF magnitude variance estimates allow ’confidence bands’ to be placed on FRF magnitude estimates, giving an indication of the variability of the result. Uncorrelated content estimates indicate sources and magnitudes of noise in the measurement system. Both Monte Carlo simulations and experimental work are used to verify the statistical and uncorrelated content estimates. Relations to extend the three-channel FRF estimator to multiple input-multiple output measurements are developed and verified through simulations.
Ph. D.
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5

Bibinger, Markus. "Estimating the quadratic covariation from asynchronous noisy high-frequency observations." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2011. http://dx.doi.org/10.18452/16365.

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Ein nichtparametrisches Schätzverfahren für die quadratische Kovariation von hochfrequent nicht-synchron beobachteter Itô-Prozessen mit einem additiven Rauschen wird entwickelt. Für eine artverwandte Folge von statistischen Experimenten wird die lokal asymptotische Normalität (LAN) im Sinne von Le Cam bewiesen. Mit dieser lassen sich optimale Konvergenzraten und Effizienzschranken für asymptotische Varianzen ableiten. Der vorgestellte Schätzer wird auf Grundlage von zwei modernen Verfahren, für die Anwendung bei nicht-synchronen Beobachtungen zum einen, und einem additiven Rauschen zum anderen, entwickelt. Der Hayashi-Yoshida Schätzer wird in einer neuen Darstellung eingeführt, welche einen Synchronisierungsalgorithmus mit einschließt, der für die kombinierte Methode ausgelegt werden kann. Es wird eine stabiles zentrales Grenzwerttheorem bewiesen, wobei spezieller Wert auf die Analyse des Einflusses der Nicht-Synchronität auf die asymptotische Varianz gelegt wird. Nach diesen Vorbereitungen wird das kombinierte Schätzverfahren für den allgemeinsten Fall nicht-synchroner verrauschter Beobachtungen vorgestellt. Dieses beruht auf Subsampling- und Multiskalenmethoden, die auf Mykland, Zhang und Aït-Sahalia zurück gehen. Es vereint positive Eigenschaften der beiden Ursprünge. Das zentrale Resultat dieser Arbeit ist der Beweis, dass der Schätzfehler stabil in Verteilung gegen eine gemischte Normalverteilung konvergiert. Für die asymptotische Varianz wird ein konsistenter Schätzer angegeben. In einer Anwendungsstudie wird eine praktische Implementierung des Schätzverfahrens, die die Wahl von abhängigen Parametern beinhaltet, getestet und auf ihre Eigenschaften im Falle endlicher Stichprobenumfänge untersucht. Neuen fortgeschrittenen Entwicklungen auf dem Forschungsfeld von Seite anderer Autoren wird Rechnung getragen durch Vergleiche und diesbezügliche Kommentare.
A nonparametric estimation approach for the quadratic covariation of Itô processes from high-frequency observations with an additive noise is developed. It is proved that a closely related sequence of statistical experiments is locally asymptotically normal (LAN) in the Le Cam sense. By virtue of this property optimal convergence rates and efficiency bounds for asymptotic variances of estimators can be concluded. The proposed nonparametric estimator is founded on a combination of two modern estimation methods devoted to an additive observation noise on the one hand and asynchronous observation schemes on the other hand. We reinvent this Hayashi-Yoshida estimator in a new illustration that can serve as a synchronization method which is possible to adapt for the combined approach. A stable central limit theorem is proved focusing especially on the impact of non-synchronicity on the asymptotic variance. With this preparations on hand, the generalized multiscale estimator for the noisy and asynchronous setting arises. This convenient method for the general model is based on subsampling and multiscale estimation techniques that have been established by Mykland, Zhang and Aït-Sahalia. It preserves valuable features of the synchronization methodology and the estimators to cope with noise perturbation. The central result of the thesis is that the estimation error of the generalized multiscale estimator converges with optimal rate stably in law to a centred mixed normal limiting distribution on fairly general regularity assumptions. For the asymptotic variance a consistent estimator based on time transformed histograms is given making the central limit theorem feasible. In an application study a practicable estimation algorithm including a choice of tuning parameters is tested for its features and finite sample size behaviour. We take account of recent advances on the research field by other authors in comparisons and notes.
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Park, Sujin. "Consistent estimator of ex-post covariation of discretely observed diffusion processes and its application to high frequency financial time series." Thesis, London School of Economics and Political Science (University of London), 2011. http://etheses.lse.ac.uk/182/.

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First chapter of my thesis reviews recent developments in the theory and practice of volatility measurement. We review the basic theoretical framework and describe the main approaches to volatility measurement in continuous time. In this literature the central parameter of interest is the integrated variance and its multivariate counterpart. We describe the measurement of these parameters under ideal circumstances and when the data are subject to measurement error, microstructure issues. We also describe some common applications of this literature. In the second chapter, we propose a new estimator of multivariate ex-post volatility that is robust to microstructure noise and asynchronous data timing. The method is based on Fourier domain techniques. The advantage of this method is that it does not require an explicit time alignment, unlike existing methods in the literature. We derive the large sample properties of our estimator under general assumptions allowing for the number of sample points for different assets to be of different order of magnitude. We show in extensive simulations that our method outperforms the time domain estimator especially when two assets are traded very asynchronously and with different liquidity. In the third chapter, we propose to model high frequency price series by a timedeformed L´evy process. The deformation function is modeled by a piecewise linear function of a physical time with a slope depending on the marks associated with intra-day transaction data. The performance of a quasi-MLE and an estimator based on a permutation-like statistic is examined in extensive simulations. We also consider estimating the deformation function nonparametrically by pulling together many time series. We show that financial returns spaced by equal elapse of estimated deformed time are homogenous. We propose an order execution strategy using the fitted deformation time
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Tjahyadi, Hendra, and hendramega@yahoo com. "Adaptive Multi Mode Vibration Control of Dynamically Loaded Flexible Structures." Flinders University. Engineering, 2006. http://catalogue.flinders.edu.au./local/adt/public/adt-SFU20070130.192707.

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In this thesis, three control methodologies are proposed for suppressing multi-mode vibration in flexible structures. Controllers developed using these methods are designed to (i) be able to cope with large and sudden changes in the system's parameters, (ii) be robust to unmodelled dynamics, and (iii) have a fast transient response. In addition, the controllers are designed to employ a minimum number of sensor-actuator pairs, and yet pose a minimum computational demand so as to allow real-time implementation. A cantilever beam with magnetically clamped loads is designed and constructed as the research vehicle for evaluation of the proposed controllers. Using this set-up, sudden and large dynamic variations of the beam loading can be tested, and the corresponding changes in the plant's parameters can be observed. Modal testing reveals that the first three modes of the plant are the most significant and need to be suppressed. It is also identified that the first and third modes are spaced more than a decade apart in frequency. The latter characteristic increases the difficulty of effectively controlling all three modes simultaneously using one controller. To overcome this problem, the resonant control method is chosen as the basis for the control methodologies discussed in this thesis. The key advantage of resonant control is that it can be tuned to provide specific attenuation only at and immediately close to the resonant frequency of concern. Consequently, it does not cause control spillover to other modes owing to unmodeled dynamics. Because of these properties, a resonant controller can be configured to form a parallel structure with the objective of targeting and cancelling multiple modes individually. This is possible regardless of the mode spacing. In addition, resonant control requires only a minimum number of collocated sensor-actuator pairs for multi-mode vibration cancellation. All these characteristics make resonant control a suitable candidate for multi-mode vibration cancellation of flexible structures. Since a resonant controller provides negligible attenuation away from the natural frequencies that it has been specifically designed for, it is very sensitive to changes of a system's natural frequencies and becomes ineffective when these mode frequencies change. Hence, for the case of a dynamically loaded structure with consequent variations in mode frequencies, the resonant control method must be modified to allow tracking of system parameter changes. This consideration forms the theme of this thesis, which is to allow adaptive multi-mode vibration control of dynamically-loaded flexible structures. Three controller design methodologies based on the resonant control principle are consequently proposed and evaluated. In the first approach, all possible loading conditions are assumed to be a priori known. Based on this assumption, a multi-model multi-mode resonant control (M4RC) method is proposed. The basis of the M4RC approach is that it comprises a bank of known loading models that are designed such that each model gives optimum attenuation for a particular loading condition. Conceptually, each model is implemented as a set of fixed-parameter controllers, one for each mode of concern. In reality, each mode controller is implemented as an adjustable resonant controller that is loaded with the fixed-model parameters of the corresponding mode. The M4RC method takes advantage of the highly frequency-sensitive nature of resonant control to allow simple and rapid selection of the optimum controller. Identification of the set of resonant frequencies is implemented using a bank of band-pass filters that correspond to the mode frequencies of the known models. At each time interval a supervisor scheme determines for each mode which model has the closest frequency to the observed vibration frequency and switches the corresponding model controller output to attenuate the mode. Selection is handled on a mode-by-mode basis, such that for each mode the closest model is selected. The proposed M4RC is relatively simple and less computationally complex compared to other multi-model methods reported in the literature. In particular, the M4RC uses a simple supervisor scheme and requires only a single controller per mode. Other multi-model methods use more complex supervision schemes and require one controller per model. The M4RC method is evaluated through both simulation and experimental studies. The results reveal that the proposed M4RC is very effective for controlling multi-mode vibration of a flexible structure with known loading conditions, but is ineffective for unmodeled loading conditions. In the second approach, the assumption that all loading conditions are a priori known is relaxed. An adaptive multi-mode resonant control (ARC) method is proposed to control the flexible structure for all possible (including unknown) loading conditions. On-line estimation of the structure's natural frequencies is used to update the adaptive resonant controller's parameters. The estimation of the natural frequencies is achieved using a parallel set of second-order recursive least-squares estimators, each of which is designed for a specific mode of concern. To optimise the estimation accuracy for each mode frequency, a different sampling rate suitable for that mode is used for the corresponding estimator. Simulation and experiment results show that the proposed adaptive method can achieve better performance, as measured by attenuation level, over its fixed-parameter counterpart for a range of unmodeled dynamics. The results also reveal that, for the same sequences of known loading changes, the transient responses of the ARC are slower than those of the M4RC. In the third approach, a hybrid multi-model and adaptive resonant control is utilized to improve the transient response of the ARC. The proposed multi-model multi-mode adaptive resonant control (M4ARC) method is designed as a combination of the M4RC and ARC methods. The basis of the proposed method is to use the M4RC fixed-parameter model scheme to deal with transient conditions while the ARC adaptive parameter estimator is still in a state of fluctuation. Then, once the estimator has reached the vicinity of its steady-state, the adaptive model is switched in place of the fixed model to achieve optimum control of the unforeseen loading condition. Whenever a loading change is experienced, the simple M4RC supervisor scheme is used to identify the closest model and to load the adjustable resonant controllers with the fixed parameters for that model. Meanwhile, the mode estimators developed for the ARC method are used to identify the exact plant parameters for the modes of concern. As soon as these parameters stop rapidly evolving and reach their steady-state, they are loaded into the respective adjustable controllers. The same process is repeated whenever a loading change occurs. Given the simplicity of the M4ARC method and its minimal computation demand, it is easily applicable for real-time implementation. Simulation and experiment results show that the proposed M4ARC outperforms both the ARC with respect to transient performance, and the M4RC with respect to unmodeled loading conditions. The outcomes of this thesis provide a basis for further development of the theory and application of active control for flexible structures with unforeseen configuration variations. Moreover, the basis for the proposed multi-model adaptive control can be used in other areas of control (not limited to vibration cancellation) where fast dynamic reconfiguration of the controller is necessary to accommodate structural changes and fluctuating external disturbances.
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Gyongy, Istvan. "Phase/amplitude estimation for tuning and monitoring." Thesis, University of Oxford, 2008. http://ora.ox.ac.uk/objects/uuid:f398b986-e8a0-403a-9118-5edae6403e00.

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The benefits of good loop tuning in the process industries have long been recognized. Ensuring that controllers are kept well-configured despite changes in process dynamics can bring energy and material savings, improved product quality as well as reduced downtime. A number of loop tuning packages therefore exist that can, on demand, check the state of a loop and adjust the controller as necessary. These methods generally apply some form of upset to the process to identify the current plant dynamics, against which the controller can then be evaluated. A simple approach to the automatic tuning of PI controllers injects variable frequency sinewaves into the loop under normal plant operation. The method employs a phase-locked loop-based device called a phase-frequency/estimation and uses 'design-point' rules, where the aim is for the Nyquist locus of the loop to pass through a particular point on the complex plane. A number of advantages are offered by the scheme: it can carry out both 'one shot' tuning and continuous adaptation, the latter even with the test signal set to a lower amplitude than that of noise. A published article is included here that extends the approach to PID controllers, with simulations studies and real-life test showing the method to work consistently well for a for a wide range of typical process dynamics, the closed-loop having a response that compares well with that produced by standard tuning rules. The associated signal processing tools are tested by applying them to the transmitter of a Coriolis mass-flow meter. Schemes are devised for the tracking and control of the second mode of measurementtube oscillation alongside the so-called 'driven mode', at which the tubes are usually vibrated, leading to useful information being made available for measurement correction purposes. Once a loop has been tuned, it is important to assess it periodically and to detect any performance losses resulting from events such as changes in process or disturbance dynamics and equipment malfunction such as faulty sensors and actuators. Motivated by the effective behaviour of the controller tuners, a loop monitor developed here, also using probing sinewaves coupled with 'design-point' ideas. In this application, the effect on the process must be minimal, so the device must work with lower still SNRs. Thus it is practical to use a fixed-frequency probing signal, together with a different tool set for tracking it. An extensive mathematical framework is developed describing the statistical properties of the signal parameter estimates, and those of the indices derived from these estimates indicating the state of the loop. The result is specific practical guidelines for the application of the monitor (e.g. for the choices of test signal amplitude and test duration). Loop monitoring itself has traditionally been carried out by passive methods that calculate various performance indicators from routine operating data. Playing a central role amongst these metrics is the Harris Index (HI) and its variants, which compare the output variance to a 'minimum achievable' figure. A key advantage of the active monitor proposed here is that it is able not only to detect suboptimal control but also to suggest how the controller should be adjusted. Moreover, the monitor’s index provides a strong indication of changes in damping factor. Through simple adjustments to the algorithm (by raising the amplitude of the test signal or adding high frequency dither to the control signal), the method can be applied even in the presence of actuator non-linearity, allowing it to identify the cause of performance losses. This is confirmed by real-life trials on a non-linear flow rig.
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Curuk, Selva Muratoglu. "Highly Efficient New Methods Of Channel Estimation For Ofdm Systems." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12609290/index.pdf.

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In the first part, the topic of average channel capacity for Orthogonal Frequency Division Multiplexing (OFDM) under Rayleigh, Rician, Nakagami-m, Hoyt, Weibull and Lognormal fading is addressed. With the assumption that channel state information is known, we deal with a lower bound for the capacity and find closed computable forms for Rician fading without diversity and with Maximum Ratio Combining diversity at the receiver. Approximate expressions are also provided for the capacity lower bound in the case of high Signal to Noise Ratio. This thesis presents two simplified Maximum A Posteriori (MAP) channel estimators to be used in OFDM systems under frequency selective slowly varying Rayleigh fading. Both estimators use parametric models, where the first model assumes exponential frequency domain correlation while the second model is based on the assumption of exponential power delay profile. Expressions for the mean square error of estimations are derived and the relation between the correlation of subchannel taps and error variance is investigated. Dependencies of the proposed estimators&rsquo
performances on the model parameter and noise variance estimation errors are analyzed. We also provide approximations on the estimators&rsquo
algorithms in order to make the estimators practical. Finally, we investigate SER performance of the simplified MAP estimator based on exponential power delay profile assumption used for OFDM systems with QPSK modulation. The results indicate that the proposed estimator performance is always better than that of the ML estimator, and as the subchannel correlation increases the performance comes closer to that of perfectly estimated channel case.
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Silva, Tiago Vieira da. "Algoritmos evolutivos como estimadores de frequência e fase de sinais elétricos: métodos multiobjetivos e paralelização em FPGAs." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-14012014-105606/.

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Este trabalho propõe o desenvolvimento de Algoritmos Evolutivos (AEs) para estimação dos parâmetros que modelam sinais elétricos (frequência, fase e amplitude) em tempo-real. A abordagem proposta deve ser robusta a ruídos e harmônicos em sinais distorcidos, por exemplo devido à presença de faltas na rede elétrica. AEs mostram vantagens para lidar com tais tipos de sinais. Por outro lado, esses algoritmos quando implementados em software não possibilitam respostas em tempo-real para uso da estimação como relé de frequência ou Unidade de Medição Fasorial. O desenvolvimento em FPGA apresentado nesse trabalho torna possível paralelizar o cálculo da estimação em hardware, viabilizando AEs para análise de sinal elétrico em tempo real. Além disso, mostra-se que AEs multiobjetivos podem extrair informações não evidentes das três fases do sistema e estimar os parâmetros adequadamente mesmo em casos em que as estimativas por fase divirjam entre si. Em outras palavras, as duas principais contribuições computacionais são: a paralelização do AE em hardware por meio de seu desenvolvimento em um circuito de FPGA otimizado a nível de operações lógicas básicas e a modelagem multiobjetiva do problema possibilitando análises dos sinais de cada fase, tanto independentemente quanto de forma agregada. Resultados experimentais mostram superioridade do método proposto em relação ao estimador baseado em transformada de Fourier para determinação de frequência e fase
This work proposes the development of Evolutionary Algorithms (EAs) for the estimation of the basic parameters from electrical signals (frequency, phase and amplitude) in real time. The proposed approach must be robust to noise and harmonics in signals distorted, for example, due to the presence of faults in the electrical network. EAs show advantages for dealing with these types of signals. On the other hand, these algorithms when implemented in software cant produce real-time responses in order to use their estimations as frequency relay or Phasor Measurement Unit. The approach developed on FPGA proposed in this work parallelizes in hardware the process of estimation, enabling analyses of electrical signals in real time. Furthermore, it is shown that multi-objective EAs can extract non-evident information from the three phases of the system and properly estimate parameters even when the phase estimates diverge from each other. This research proposes: the parallelization of an EA in hardware through its design on FPGA circuit optimized at level of basic logic operations and the modeling of the problem enabling multi-objective analyses of the signals from each phase in both independent and aggregate ways. Experimental results show the superiority of the proposed method compared to an estimator based on Fourier transform for determining frequency and phase
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Books on the topic "Frequency estimator"

1

Swain, A. K. Weighted complex orthogonal estimator for identifying linear and nonlinear continuous time models from generalised frequency response functions. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1995.

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Swagata, Nandi, and SpringerLink (Online service), eds. Statistical Signal Processing: Frequency Estimation. India: Springer India, 2012.

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Kane, Douglas L. Flood frequency estimation for Alaska. [Fairbanks, Alaska]: Alaska Division of Geological and Geophysical Surveys, 1989.

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Jacob, Florian. Risk Estimation on High Frequency Financial Data. Wiesbaden: Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-09389-1.

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Engle, R. F. The econometrics of ultra-high frequency data. Cambridge, MA: National Bureau of Economic Research, 1996.

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Time-frequency analysis and synthesis of linear signal spaces: Time-frequency filters, signal detection and estimation, and range-Doppler estimation. Boston: Kluwer Academic Publishers, 1998.

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Hlawatsch, F. Time-Frequency Analysis and Synthesis of Linear Signal Spaces: Time-Frequency Filters, Signal Detection and Estimation, and Range-Doppler Estimation. Boston, MA: Springer US, 1998.

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Aït-Sahalia, Yacine. Ultra high frequency volatility estimation with dependent microstructure noise. Cambridge, MA: National Bureau of Economic Research, 2005.

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Aït-Sahalia, Yacine. Ultra high frequency volatility estimation with dependent microstructure noise. Cambridge, Mass: National Bureau of Economic Research, 2005.

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Aït-Sahalia, Yacine. High frequency market microstructure noise estimates and liquidity measures. Cambridge, MA: National Bureau of Economic Research, 2008.

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Book chapters on the topic "Frequency estimator"

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Ganguly, Sumit. "Taylor Polynomial Estimator for Estimating Frequency Moments." In Automata, Languages, and Programming, 542–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-47672-7_44.

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Benesty, Jacob. "Best Speech Enhancement Estimator in the Frequency Domain." In Fundamentals of Speech Enhancement, 5–22. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74524-4_2.

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Hoeher, Peter. "An Adaptive Channel Estimator for Frequency-Selective Fading Channels." In ASST ’90 7. Aachener Symposium für Signaltheorie, 168–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-76062-4_28.

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Hansen, Peter Reinhard, Guillaume Horel, Asger Lunde, and Ilya Archakov. "A Markov Chain Estimator of Multivariate Volatility from High Frequency Data." In The Fascination of Probability, Statistics and their Applications, 361–94. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25826-3_17.

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Bro, P. B., C. Rosenberger, H. Laurent, C. Gaete-Eastman, M. Fernández, and M. A. Moya-León. "A support vector machine as an estimator of mountain papaya ripeness using resonant frequency or frequency centroid." In IFIP International Federation for Information Processing, 335–44. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/978-0-387-34747-9_35.

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Minal, Saxena, and Khare Kavita. "VHDL Based Analysis of the Channel Estimator Algorithm and Frequency Offset Estimation for OFDM System." In Mobile Communication and Power Engineering, 424–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35864-7_64.

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Shendge, P. D., B. M. Patre, and S. B. Phadke. "Robust Load Frequency Sliding Mode Control Based on Uncertainty and Disturbance Estimator." In Lecture Notes in Electrical Engineering, 361–74. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74905-1_26.

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Zhou, Si-Da, Ward Heylen, Paul Sas, and Li Liu. "Time-Frequency Domain Modal Parameter Estimation of Time-Varying Structures Using a Two-Step Least Square Estimator." In Topics in Modal Analysis I, Volume 5, 65–75. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-2425-3_8.

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Suk, Soo-Young, Hyun-Yeol Chung, and Hiroaki Kojima. "Voice/Non-Voice Classification Using Reliable Fundamental Frequency Estimator for Voice Activated Powered Wheelchair Control." In Embedded Software and Systems, 347–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72685-2_33.

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Park, Sangwook, Chul Jin Cho, Younglo Lee, Andrew Da Costa, SangHo Lee, and Hanseok Ko. "Bayesian Estimator Based Target Localization in Ship Monitoring System Using Multiple Compact High Frequency Surface Wave Radars." In Lecture Notes in Electrical Engineering, 157–67. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90509-9_9.

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Conference papers on the topic "Frequency estimator"

1

Annaswamy, A. M., N. Ho, C. Cao, and A. Kojic. "A convergent frequency estimator." In Proceedings of 2000 American Control Conference (ACC 2000). IEEE, 2000. http://dx.doi.org/10.1109/acc.2000.878577.

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Miao, Yongchun, Haixin Sun, and Junfeng Wang. "Anisotropic Instantaneous Frequency Estimator." In 2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2019. http://dx.doi.org/10.1109/icspcc46631.2019.8960716.

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Kohda, Tohru, Koh Ogiwara, M. Tahir Abbas Khan, and Kazuyuki Aihara. "Frequency estimator using Newton's method." In Applications (ISSSTA). IEEE, 2010. http://dx.doi.org/10.1109/isssta.2010.5651333.

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Kewu Peng, Aolin Xu, and Zhixing Yang. "Optimal correlation based frequency estimator with maximal estimation range." In 2008 International Conference on Communications, Circuits and Systems (ICCCAS). IEEE, 2008. http://dx.doi.org/10.1109/icccas.2008.4657772.

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Adachi, Kentaro, Haruo Suemitsu, and Takami Matsuo. "LMI-Based Frequency Estimator with Averaging." In Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007). IEEE, 2007. http://dx.doi.org/10.1109/icicic.2007.370.

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Xiao, Yangcan, and Ping Wei. "A New Effective Single Frequency Estimator." In 2006 International Conference on Communications, Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/icccas.2006.284710.

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Bobtsov, Alexey A., and Darina A. Romasheva. "Frequency estimator of a biased sinusoid." In 2007 46th IEEE Conference on Decision and Control. IEEE, 2007. http://dx.doi.org/10.1109/cdc.2007.4434188.

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Nielsen, Jesper Kjaer, Mads Graesboll Christensen, and Soren Holdt Jensen. "An approximate Bayesian fundamental frequency estimator." In ICASSP 2012 - 2012 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2012. http://dx.doi.org/10.1109/icassp.2012.6288947.

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Le Gall, Herve, Rshdee Alhakim, Miroslav Valka, Salvador Mir, Haralampos-G. Stratigopoulos, and Emmanuel Simeu. "High frequency jitter estimator for SoCs." In 2015 20th IEEE European Test Symposium (ETS). IEEE, 2015. http://dx.doi.org/10.1109/ets.2015.7138760.

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Wu, Yun, Hanwen Luo, Ming Ding, and Chongguang Yan. "A Novel Frequency Offset Estimator for OFDM." In 2006 International Conference on Communications, Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/icccas.2006.284829.

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Reports on the topic "Frequency estimator"

1

Li, Ta-Hsin, Benjamin Kedem, and Sid Yakowitz. Asymptotic Normality of the Contraction Mapping Estimator for Frequency Estimation. Fort Belvoir, VA: Defense Technical Information Center, September 1991. http://dx.doi.org/10.21236/ada453892.

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Kane, D. L., and J. R. Janowicz. Flood frequency estimation for Alaska. Alaska Division of Geological & Geophysical Surveys, 1988. http://dx.doi.org/10.14509/2465.

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Eide, S. A., S. T. Khericha, M. B. Calley, D. A. Johnson, and M. L. Marteeny. Component external leakage and rupture frequency estimates. Office of Scientific and Technical Information (OSTI), November 1991. http://dx.doi.org/10.2172/10140552.

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Eide, S. A., S. T. Khericha, M. B. Calley, D. A. Johnson, and M. L. Marteeny. Component external leakage and rupture frequency estimates. Office of Scientific and Technical Information (OSTI), November 1991. http://dx.doi.org/10.2172/5461408.

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Rice, Michael, and Erik Perrins. On Frequency Offset Estimation Using the iNET Preamble in Frequency Selective Fading Channels. Fort Belvoir, VA: Defense Technical Information Center, March 2014. http://dx.doi.org/10.21236/ada622041.

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Kao, Shih-Chieh, and Scott Deneale. Application of Point Precipitation Frequency Estimates to Watersheds. Office of Scientific and Technical Information (OSTI), February 2021. http://dx.doi.org/10.2172/1808414.

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Varshney, Pramod K., Donald D. Welner, and Tzeta Tsao. Radar Signal Detection and Estimation Using Time-Frequency Distributions. Fort Belvoir, VA: Defense Technical Information Center, October 1995. http://dx.doi.org/10.21236/ada304818.

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Ait-Sahalia, Yacine, Per Mykland, and Lan Zhang. Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise. Cambridge, MA: National Bureau of Economic Research, May 2005. http://dx.doi.org/10.3386/w11380.

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Ait-Sahalia, Yacine, and Jialin Yu. High Frequency Market Microstructure Noise Estimates and Liquidity Measures. Cambridge, MA: National Bureau of Economic Research, February 2008. http://dx.doi.org/10.3386/w13825.

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Young, Craig. Problematic plant monitoring in Hopewell Culture National Historical Park: 2008–2019. Edited by Tani Hubbard. National Park Service, July 2021. http://dx.doi.org/10.36967/nrr-2286658.

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Managers are challenged with the impact of problematic plants, including exotic, invasive, and pest plant species. Information on the cover and frequency of these plants is essential for developing risk-based approaches to managing these species. Based on surveys conducted in 2008, 2011, 2015, and 2019, Heartland Network staff and contractors identified a cumulative total of 51 potentially problematic plant species in Hopewell Culture National Historical Park. Of the 37 species found in 2019, we characterized 7 as very low frequency, 9 as low frequency, 17 as medium frequency, and 4 as high frequency. Of these, midpoint cover estimates of 2 medium frequency and 2 high frequency species exceeded the 10-acre threshold. Because of the number, extent, and cover of problematic plants in the park and the small park size, control efforts should focus on treating high priority species across the entire park. High priority species may include plant species capable of rapid spread, species at low population levels, and species which can effectively be controlled.
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