Estimation of quantities determined as implicit functions of unknown parameters

Metrika ◽  
2009 ◽  
Vol 71 (3) ◽  
pp. 353-359 ◽  
Author(s):  
Jie Mi
Keyword(s):  
Implicit Functions ◽  
Unknown Parameters

Graphic method for assessing the margins of resistance to acoustic vibrations in the chambers of rocket engines by combustion noise

2020 ◽  
pp. 15-21
Author(s):  
R.A. Tsarapkin ◽  
V.N. Ivanov ◽  
V.I. Biryukov
Keyword(s):  
Rocket Engine ◽  
Spectral Characteristics ◽  
Combustion Process ◽  
Combustion Noise ◽  
Rocket Engines ◽  
Acoustic Vibrations ◽  
Statistical Regression ◽  
Unknown Parameters ◽  
Damping Decrement ◽  
Resonance Frequencies

An experimental method is proposed for estimating the damping decrements of pressure fluctuations in the combustion chambers of forced rocket engines. The method is based on the statistical processing of noise pressure pulsations in the vicinity of natural resonance frequencies for normal modes of acoustic vibrations of the reaction volume and the subsequent prediction of the instability of the combustion process relative to acoustic vibrations. Based on the theory of statistical regression for multidimensional experimental data, the problem of predicting unknown parameters of sample distributions is solved by asymptotic determination of the correlation coefficient of the damping decrement of pressure vibrations through optimal linear predictors and the Kolmogorov distribution. Keywords rocket engine, combustion chamber, acoustic vibrations, combustion noise, spectral characteristics, Kolmogorov criterion, damping decrement. [email protected]

SPACE SURVEILLANCE SYSTEM’S SAR SIGNAL DETECTION RESULTS

2018 ◽  
pp. 63-68 ◽  
Author(s):  
A. V. Ksendzuk ◽  
A. A. Kanatchikov ◽  
P. A. Gerasimov
Keyword(s):  
Signal Detection ◽  
Surveillance System ◽  
Observation Interval ◽  
Pulse Repetition Frequency ◽  
Storage Device ◽  
Periodic Signal ◽  
Unknown Parameters ◽  
Software Optimization ◽  
Space Objects ◽  
Field Programmable

Special aspects of space objects radiotechnical surveillance system used for filling the space tracking and surveillance system (STSS) satellite catalogue described and analyzed. Special emphasis placed on spaceborne synthetic aperture radar signals detection. Parameters of the SAR signals estimated with the proposed radiotechnical surveillance system described. Two processing methods for unknown and partially known signals proposed and analyzed. Signal detection with incompletely known parameters performs with cumulative second-order statistic. Signal detection with unknown parameters performs for periodic signal in assumption that observation interval exceed pulse repetition frequency. Proposed methods implemented in hardware demonstrator of radiotechnical surveillance system. This demonstrator works in real-time on Field Programmable Gate Array or save data on storage device for post-processing. L-band Palsar2 signal detection results presented and analyzed. Further work for hardware and software optimization described.

An experimental method for evaluating constitutive models of myocardium in in vivo hearts

1994 ◽  
Vol 267 (2) ◽  
pp. H853-H863 ◽  
Author(s):  
L. L. Creswell ◽  
M. J. Moulton ◽  
S. G. Wyers ◽  
J. S. Pirolo ◽  
D. S. Fishman ◽  
...  
Keyword(s):  
Experimental Method ◽  
Diastolic Pressure ◽  
Constitutive Models ◽  
Fe Analysis ◽  
Small Displacement ◽  
Ventricular Wall ◽  
Canine Heart ◽  
Unknown Parameters ◽  
Tissue Tagging

A new experimental method for the evaluation of myocardial constitutive models combines magnetic resonance (MR) radiofrequency (RF) tissue-tagging techniques with iterative two-dimensional (2-D) nonlinear finite element (FE) analysis. For demonstration, a nonlinear isotropic constitutive model for passive diastolic expansion in the in vivo canine heart is evaluated. A 2-D early diastolic FE mesh was constructed with loading parameters for the ventricular chambers taken from mean early diastolic-to-late diastolic pressure changes measured during MR imaging. FE solution was performed for regional, intramyocardial ventricular wall strains using small-strain, small-displacement theory. Corresponding regional ventricular wall strains were computed independently using MR images that incorporated RF tissue tagging. Two unknown parameters were determined for an exponential strain energy function that maximized agreement between observed (from MR) and predicted (from FE analysis) regional wall strains. Extension of this methodology will provide a framework in which to evaluate the quality of myocardial constitutive models of arbitrary complexity on a regional basis.

scholarly journals Adaptive Control of a Vehicular Platoon with Unknown Parameters and Input Variations

2020 ◽  
Vol 53 (2) ◽  
pp. 13876-13881
Author(s):  
Mohammad Pourmahmood Aghababa ◽  
Mehrdad Saif ◽  
Bahram Shafai
Keyword(s):  
Adaptive Control ◽  
Unknown Parameters

THE IMPACTS OF INDIVIDUAL INFORMATION ON LOSS RESERVING

2020 ◽  
pp. 1-45
Author(s):  
Zhigao Wang ◽  
Xianyi Wu ◽  
Chunjuan Qiu
Keyword(s):  
Information Model ◽  
Statistical Properties ◽  
Unknown Parameters ◽  
Asymptotic Behaviors ◽  
Computation Procedure ◽  
General Insurance ◽  
Loss Reserving ◽  
Portfolio Size ◽  
Better Than ◽  
Individual Information

Abstract The projection of outstanding liabilities caused by incurred losses or claims has played a fundamental role in general insurance operations. Loss reserving methods based on individual losses generally perform better than those based on aggregate losses. This study uses a parametric individual information model taking not only individual losses but also individual information such as age, gender, and so on from policies themselves into account. Based on this model, this study proposes a computation procedure for the projection of the outstanding liabilities, discusses the estimation and statistical properties of the unknown parameters, and explores the asymptotic behaviors of the resulting loss reserving as the portfolio size approaching infinity. Most importantly, this study demonstrates the benefits of individual information on loss reserving. Remarkably, the accuracy gained from individual information is much greater than that from considering individual losses. Therefore, it is highly recommended to use individual information in loss reserving in general insurance.

Inverse problems for finite Jacobi matrices and Krein–Stieltjes strings

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Alexander Mikhaylov ◽  
Victor Mikhaylov
Keyword(s):  
Dynamical System ◽  
Inverse Problems ◽  
Jacobi Matrix ◽  
Jacobi Matrices ◽  
Unknown Parameters ◽  
Stieltjes String ◽  
Propagation Of Waves ◽  
Dynamic Inverse

Abstract We consider dynamic inverse problems for a dynamical system associated with a finite Jacobi matrix and for a system describing propagation of waves in a finite Krein–Stieltjes string. We offer three methods of recovering unknown parameters: entries of a Jacobi matrix in the first problem and point masses and distances between them in the second, from dynamic Dirichlet-to-Neumann operators. We also answer a question on a characterization of dynamic inverse data for these two problems.

scholarly journals Empirical Stochastic Model of Multi-GNSS Measurements

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4566
Author(s):  
Dominik Prochniewicz ◽  
Kinga Wezka ◽  
Joanna Kozuchowska
Keyword(s):  
Stochastic Model ◽  
Density Ratio ◽  
Functional Model ◽  
Optimal Solution ◽  
Global Navigation Satellite Systems ◽  
Unknown Parameters ◽  
Short Baseline ◽  
Stochastic Parameters ◽  
Dependent Model ◽  
The Impact

The stochastic model, together with the functional model, form the mathematical model of observation that enables the estimation of the unknown parameters. In Global Navigation Satellite Systems (GNSS), the stochastic model is an especially important element as it affects not only the accuracy of the positioning model solution, but also the reliability of the carrier-phase ambiguity resolution (AR). In this paper, we study in detail the stochastic modeling problem for Multi-GNSS positioning models, for which the standard approach used so far was to adopt stochastic parameters from the Global Positioning System (GPS). The aim of this work is to develop an individual, empirical stochastic model for each signal and each satellite block for GPS, GLONASS, Galileo and BeiDou systems. The realistic stochastic model is created in the form of a fully populated variance-covariance (VC) matrix that takes into account, in addition to the Carrier-to-Noise density Ratio (C/N0)-dependent variance function, also the cross- and time-correlations between the observations. The weekly measurements from a zero-length and very short baseline are utilized to derive stochastic parameters. The impact on the AR and solution accuracy is analyzed for different positioning scenarios using the modified Kalman Filter. Comparing the positioning results obtained for the created model with respect to the results for the standard elevation-dependent model allows to conclude that the individual empirical stochastic model increases the accuracy of positioning solution and the efficiency of AR. The optimal solution is achieved for four-system Multi-GNSS solution using fully populated empirical model individual for satellite blocks, which provides a 2% increase in the effectiveness of the AR (up to 100%), an increase in the number of solutions with errors below 5 mm by 37% and a reduction in the maximum error by 6 mm compared to the Multi-GNSS solution using the elevation-dependent model with neglected measurements correlations.

Uniformly ultimately bounded tracking control of sandwich systems with nonsymmetric sandwiched dead-zone nonlinearity and input saturation constraint

2021 ◽  
pp. 107754632098794
Author(s):  
Meysam Azhdari ◽  
Tahereh Binazadeh
Keyword(s):  
Dead Zone ◽  
Input Saturation ◽  
Closed Loop System ◽  
Unknown Parameters ◽  
External Disturbances ◽  
Uniformly Ultimately Bounded ◽  
Output Tracking ◽  
Saturation Constraint ◽  
Two Phases ◽  
Practical Constraints

This article studies the uniformly ultimately bounded output tracking problem of uncertain nonlinear sandwich systems with sandwiched dead-zone nonlinearity in the presence of some practical constraints such as nonsymmetric input saturation, model uncertainties, time-varying external disturbances, and unknown parameters. Due to the existence of both dead-zone and saturation nonlinearities, the design process is more complicated; therefore, to solve the design complexities, the designing process is divided into two phases. The proposed method leads to output tracking with acceptable accuracy. Moreover, all signals in the closed-loop system are ultimately bounded. Simulation results illustrate the applicability and effectiveness of the proposed method by its application on two practical sandwich systems (robotic system and electrohydraulic servo press system).

scholarly journals New Method for Generating New Families of Distributions

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 726
Author(s):  
Lamya A. Baharith ◽  
Wedad H. Aljuhani
Keyword(s):  
Exponential Distribution ◽  
Real Data ◽  
Rate Function ◽  
New Method ◽  
Likelihood Method ◽  
Alpha Power ◽  
Unknown Parameters ◽  
Failure Rate Function ◽  
New Approach ◽  
Numerical Studies

This article presents a new method for generating distributions. This method combines two techniques—the transformed—transformer and alpha power transformation approaches—allowing for tremendous flexibility in the resulting distributions. The new approach is applied to introduce the alpha power Weibull—exponential distribution. The density of this distribution can take asymmetric and near-symmetric shapes. Various asymmetric shapes, such as decreasing, increasing, L-shaped, near-symmetrical, and right-skewed shapes, are observed for the related failure rate function, making it more tractable for many modeling applications. Some significant mathematical features of the suggested distribution are determined. Estimates of the unknown parameters of the proposed distribution are obtained using the maximum likelihood method. Furthermore, some numerical studies were carried out, in order to evaluate the estimation performance. Three practical datasets are considered to analyze the usefulness and flexibility of the introduced distribution. The proposed alpha power Weibull–exponential distribution can outperform other well-known distributions, showing its great adaptability in the context of real data analysis.

Stable Calibrations of Six-DOF Serial Robots by Using Identification Models with Equalized Singular Values

Robotica ◽  
2021 ◽  
pp. 1-22
Author(s):  
Zhouxiang Jiang ◽  
Min Huang
Keyword(s):  
Industrial Robot ◽  
Singular Values ◽  
Calibration Method ◽  
Identification Accuracy ◽  
Condition Numbers ◽  
Measurement Instruments ◽  
Unknown Parameters ◽  
Calibration Methods ◽  
Six Dof ◽  
The Stability

SUMMARY In typical calibration methods (kinematic or non-kinematic) for serial industrial robot, though measurement instruments with high resolutions are adopted, measurement configurations are optimized, and redundant parameters are eliminated from identification model, calibration accuracy is still limited under measurement noise. This might be because huge gaps still exist among the singular values of typical identification Jacobians, thereby causing the identification models ill conditioned. This paper addresses such problem by using new identification models established in two steps. First, the typical models are divided into the submodels with truncated singular values. In this way, the unknown parameters corresponding to the abnormal singular values are removed, thereby reducing the condition numbers of the new submodels. However, these models might still be ill conditioned. Therefore, the second step is to further centralize the singular values of each submodel by using a matrix balance method. Afterward, all submodels are well conditioned and obtain much higher observability indices compared with those of typical models. Simulation results indicate that significant improvements in the stability of identification results and the identifiability of unknown parameters are acquired by using the new identification submodels. Experimental results indicate that the proposed calibration method increases the identification accuracy without incurring additional hardware setup costs to the typical calibration method.

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