Comparative Analysis of Three Algorithms for Two-Channel Common Frequency Sinewave Parameter Estimation: Ellipse Fit, Seven Parameter Sine Fit and Spectral Sinc Fit

2010 ◽  
Vol 17 (2) ◽  
pp. 255-270 ◽  
Author(s):  
Pedro Ramos ◽  
Fernando Janeiro ◽  
Tomáš Radil
Keyword(s):  
Parameter Estimation ◽  
Comparative Analysis ◽  
Eddy Currents ◽  
Radio Receiver ◽  
Comparison Analysis ◽  
Laser Anemometry ◽  
Signal Parameters ◽  
Sine Signal ◽  
The Time Domain ◽  
Fitting In

Comparative Analysis of Three Algorithms for Two-Channel Common Frequency Sinewave Parameter Estimation: Ellipse Fit, Seven Parameter Sine Fit and Spectral Sinc FitIn this paper, a comparison analysis of three different algorithms for the estimation of sine signal parameters in two-channel common frequency situations is presented. The relevance of this situation is clearly understood in multiple applications where the algorithms have been applied. They include impedance measurements, eddy currents testing, laser anemometry and radio receiver testing for example. The three algorithms belong to different categories because they are based on different approaches. The ellipse fit algorithm is a parametric fit based on the XY plot of the samples of both signals. The seven parameter sine fit algorithm is a least-squares algorithm based on the time domain fitting of a single tone sinewave model to the acquired samples. The spectral sinc fit performs a fitting in the frequency domain of the exact model of an acquired sinewave on the acquired spectrum. Multiple simulation situations and real measurements are included in the comparison to demonstrate the weaknesses and strong points of each algorithm.

scholarly journals Comparison analysis of using micrometers and strain gauges for measuring deformations and loads in the method of monitoring the stress-strain state

2021 ◽  
Vol 18 (3) ◽  
pp. 71-75
Author(s):  
M. O. Lobovskiy ◽  
◽  
A. L. Tukkiya ◽  
P. A. Pyatkin ◽  
◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Strain Gauge ◽  
Laboratory Tests ◽  
Strain State ◽  
Field Tests ◽  
Strain Gauges ◽  
Construction Site ◽  
Comparison Analysis ◽  
Stress Strain ◽  
Stress Strain State

The micrometer method for measuring deformations and loads in bar elements has proved to be effective not only in laboratory tests, but also in field tests on a real construction site. Having carried out a comparative analysis of the method proposed by the authors for monitoring the stress-strain state (SSS) with the strain gauge method which is widely used at present, the authors have proved that the method for measuring deformations and loads using a micrometer is not inferior in accuracy to the strain gauge method, although it is much cheaper.

scholarly journals Coherent Signal Parameter Estimation by Exploiting Decomposition of Tensors

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Long Liu ◽  
Ling Wang ◽  
Yuexian Wang ◽  
Jian Xie ◽  
Zhaolin Zhang
Keyword(s):  
Parameter Estimation ◽  
Algebraic Method ◽  
Coherent Signals ◽  
Coherent Signal ◽  
Signal Parameters ◽  
Key Innovation ◽  
Canonical Polyadic Decomposition ◽  
New Perspective ◽  
Array Aperture ◽  
Value Decomposition

The problem of parameter estimation of coherent signals impinging on an array with vector sensors is considered from a new perspective by means of the decomposition of tensors. Signal parameters to be estimated include the direction of arrival (DOA) and the state of polarization. In this paper, mild deterministic conditions are used for canonical polyadic decomposition (CPD) of the tensor-based signal model; i.e., the factor matrices can be recovered, as long as the matrices satisfy the requirement that at least one is full column rank. In conjoint with the estimation of signal parameters via the algebraic method, the DOAs and polarization parameters of coherent signals can be resolved by virtue of the first and second factor matrices. Hereinto, the key innovation of the proposed approach is that the proposed approach can effectively estimate the coherent signal parameters without sacrificing the array aperture. The superiority of the proposed algorithm is shown by comparing with the algorithms based on higher order singular value decomposition (HOSVD) and Toeplitz matrix. Theoretical and numerical simulations demonstrate the effectiveness of the proposed approach.

A New Cost Function for Parameter Estimation of Chaotic Systems Using Return Maps as Fingerprints

2014 ◽  
Vol 24 (10) ◽  
pp. 1450134 ◽  
Author(s):  
Sajad Jafari ◽  
Julien C. Sprott ◽  
Viet-Thanh Pham ◽  
S. Mohammad Reza Hashemi Golpayegani ◽  
Amir Homayoun Jafari
Keyword(s):  
Parameter Estimation ◽  
Cost Function ◽  
Chaotic Systems ◽  
Time Series Data ◽  
Initial Conditions ◽  
Model Systems ◽  
Series Data ◽  
Return Maps ◽  
Active Interest ◽  
The Time Domain

Estimating parameters of a model system using observed chaotic scalar time series data is a topic of active interest. To estimate these parameters requires a suitable similarity indicator between the observed and model systems. Many works have considered a similarity measure in the time domain, which has limitations because of sensitive dependence on initial conditions. On the other hand, there are features of chaotic systems that are not sensitive to initial conditions such as the topology of the strange attractor. We have used this feature to propose a new cost function for parameter estimation of chaotic models, and we show its efficacy for several simple chaotic systems.

scholarly journals Hydrological model performance and parameter estimation in the wavelet-domain

2009 ◽  
Vol 6 (2) ◽  
pp. 2451-2498 ◽  
Author(s):  
B. Schaefli ◽  
E. Zehe
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
Time Domain ◽  
Model Performance ◽  
Time Varying ◽  
Wavelet Domain ◽  
Frequency Content ◽  
Time Varying Frequency ◽  
The Time Domain

Abstract. This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series) of a simulated discharge series to the one of the corresponding observed time series. As discussed in this paper, calibrating hydrological models so as to reproduce the time-varying frequency content of the observed signal can lead to different results than parameter estimation in the time-domain. Therefore, wavelet-domain parameter estimation has the potential to give new insights into model performance and to reveal model structural deficiencies. We apply the proposed method to synthetic case studies and a real-world discharge modeling case study and discuss how model diagnosis can benefit from an analysis in the wavelet-domain. The results show that for the real-world case study of precipitation – runoff modeling for a high alpine catchment, the calibrated discharge simulation captures the dynamics of the observed time series better than the results obtained through calibration in the time-domain. In addition, the wavelet-domain performance assessment of this case study highlights which frequencies are not well reproduced by the model, which gives specific indications about how to improve the model structure.

scholarly journals Theoretical Limits of Parameter Estimation Based on Quantized Data

2017 ◽  
Vol 61 (4) ◽  
pp. 312
Author(s):  
Tamás Virosztek ◽  
István Kollár
Keyword(s):  
Parameter Estimation ◽  
Transfer Characteristic ◽  
Analog Signal ◽  
Complex Signal ◽  
Measurement Technology ◽  
Ml Estimation ◽  
Analog To Digital ◽  
Signal Parameters ◽  
Band Limited ◽  
And Control

Parameter estimation of band-limited periodic signals (sine and multisine waves) is a very common task in the field of measurement technology and control engineering. In the overwhelming majority of data acquisition and control systems the analog signals of the real world are sampled an quantized using analog-to-digital converters (ADCs). To estimate the parameters of the analog signal and the parameters of the quantizer from the same measurement record is an obvious need in these cases. The parameters of the recorded signal can be used to calculate the response of our system (e.g. signals of the actuators) while the parameters of the quantizer can be used to identify the transfer characteristic of the measurement channel. Maximum likelihood (ML) estimation of the quantizer and analog signal parameters has been developed to perform this task and to provide asymptotically unbiased and efficient estimators for the quantizer and signal parameters. This paper investigates the theoretical limits of this kind of estimation: provides the Cramér-Rao Lower Bound (CRLB) for the covariance of the achieved estimators and compares them to CRLB values obtained using less complex signal and channel models. This article also provides a comparison of the empirical covariance of estimator populations achieved different ways to the CRLB of estimation. The major tendencies are drawn and explanation for them is provided as well.

Application of n-Fold Rotational Symmetries to Eddy Currents Integral Model in the Time Domain

2020 ◽  
Vol 56 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Guglielmo Rubinacci ◽  
Antonello Tamburrino ◽  
Salvatore Ventre ◽  
Fabio Villone
Keyword(s):  
Time Domain ◽  
Eddy Currents ◽  
Integral Model ◽  
The Time Domain
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