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In this investigation, compressed sensing (CS) is utilized to examine the sparsity of ultrasonic NDE signal, which consequently improves the efficacy of data sampling with significant lower rate than the Nyquist rate. The time-of-arrivals (TOAs) and amplitudes of dominant echoes are estimated through annihilating filter in the CS via matrix operation. The matrix size is proportional to the number...
A hierarchical model is presented for the implementation of a qualitative assessment of the system's operability. The system consists of objects. Objects are characterized by their parameters. The estimation is based on the determination of the state of the parameters. The procedure is carried out by introducing intermediate scales of numerical estimation. Qualitative assessments are aligned with...
This study considers the parameter estimation problem for an elaborate nonlinear hybrid model of a McKibben pneumatic artificial muscle (PAM) actuated by a proportional-directional control valve and proposes an efficient particle-swarm-optimization-based algorithm to find adequate model parameters in terms of model accuracy and computation time. A novel approach to making an algorithm more efficient...
Using atomic force microscopy (AFM) for studying soft, biological material has become increasingly popular in recent years. New approaches allow the use of recursive least squares estimation to identify the viscoelastic properties of a sample in AFM. As long as the regressor vector is persistently exciting (PE), exponential convergence of the parameters to be identified can be guaranteed. However,...
Aim at handling complicated maneuvers or other unpredicted emergencies, an estimation method of aerodynamic parameter via the Cubature Kalman Filter/Smoother (CKF/S) is proposed for maneuvering reentry vehicle (MaRV) tracking. The aerodynamic model is deduced in order to define the aerodynamic parameter at first. Secondly, the statistical properties of aerodynamic parameters are described by first-order...
In this paper, an improved estimation of distribution algorithm (EDA) is proposed and applied to the identification of ARMA model parameters. The system parameter identification problem is transformed into the optimization problem in high dimensional parameter space. Based on the traditional EDA algorithm, the parameters of preliminary estimation and data selection are added to improve the speed of...
While Golomb-Rice codes are optimal for geometrically distributed source, the practically achievable coding efficiency depends on the accuracy of the coding parameter estimated from the input data. Most existing methods are based on the assumption of geometric distribution and thus would suffer from a loss in coding efficiency if the underlying distribution deviates from the geometric distribution,...
With more degrees of freedom in the along-track axis, multichannel SAR systems are widely investigated for the purpose of ground moving target indication and motion parameter estimation. However, since conventional multichannel SAR system usually works at the side-looking mode and only the radial velocity is considered, it fails to detect targets only moving in azimuth. In this paper, the variable-boresight...
Algorithms for estimating the symbol rate of signals with modulation types M-PSK and M-FSK are presented. The algorithm for estimating the symbol rate of the M-PSK signals is based on the Fourier transform of the squares of the modules of the complex envelope of the signal. The algorithm for estimating the symbol rate of M-FSK signals is based on the separation of the spectrum of the original signal...
The problem of estimating parameters of switched affine systems with noisy input-output observations is considered. A subspace technique is proposed to exploit the observations' permutation structure, which transforms the problem of associating observations with subsystems into one of de-permutating a block diagonal matrix. Then a spectral clustering algorithm is presented to recover the block structure...
Friction modeling plays a very important role in control and simulation systems. A lot of dynamic models are proposed to capture most of the friction behavior observed experimentally. Most dynamic models are typically considered to be dependent only on relative speed and relative displacement of contacting surfaces. However, it is known that dynamic characteristics of friction are affected by other...
In this paper, a model-based control strategy is used for a networked control system. In place of a randomly estimated model of the plant, a model is determined using recursive least square estimation based on estimated states. The idea of model-based control is to reduce communication frequency, to meet the constraints of available bandwidth. It is noticed that smaller the error between plant and...
The realization of adaptive-based controllers in many industrial control applications may exhibit the parametric drift behavior acquiring the well known bursting phenomenon. In this work, an original and novel technique is proposed to eliminate this phenomenon. It is based on a modification of the discrete-time delta modulator into its continuous-time domain and then by adding hysteresis. To verify...
In this work, the modulating functions method is proposed for estimating coefficients in higher-order nonlinear partial differential equation which is the fifth order Kortewegde Vries (KdV) equation. The proposed method transforms the problem into a system of linear algebraic equations of the unknowns. The statistical properties of the modulating functions solution are described in this paper. In...
We study optimal input design and bias-compensating parameter estimation methods for continuous-time models applied on a mechanical laboratory experiment. Within this task we compare two online estimation methods that are based on Poisson moment functions with focus on quantized system outputs due to an angular encoder: The standard recursive least-squares (RLS) approach and a bias-compensating recursive...
In order to describe the highly scattered property of millimeter wave (mmWave) multiple-input multiple-output (MIMO) channels, the existing high resolution frequency domain space-alternating generalized expectation-maximization (FD-SAGE) algorithm is studied and extended to three-dimentional (3D) MIMO case by including the estimation of elevation angles. The signal model and estimation procedure are...
Acquisition of parameters for the Bidirectional Scattering Surface Reflectance Distribution Function (BSSRDF) has significant meanings in the study of computer graphics and vision research field. In this paper, we present an inverse rendering approach combined with a newly developed BSSRDF model, directional dipole model, for parameter estimation. To validate our algorithm, we estimate parameters...
We consider the problem of parameter estimation under a sequential framework. Specifically we assume that an i.i.d. random process is observed sequentially with its common pdf having a random parameter that must be estimated. We are interested in designing a stopping time that will decide when is the best moment to stop sampling the process and an estimator that will use the acquired samples in order...
This paper presents some experiences concerning the testing of generating units response to frequency transient. The tests have been performed both for modeling and monitoring the compliance of the settings of the generating units with the operational requirements. A test methodology, based on mathematical modeling, is developed and proposed. The approach is intended to interfere (or disturb) less...
In this paper, we investigate the prediction of mobile MIMO channels with varying multipath parameters. Based on the PAST algorithm, we propose a multidimensional adaptive ESPRIT approach for jointly tracking the evolution of the Doppler frequencies and spatial directions of arrival and departure of the propagation paths. Future states of the channel are predicted using the last estimate of the propagation...
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