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Search results for: LEAST SQUARES
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SELECTION OF REFERENCE PLANE BY THE LEAST SQUARES FITTING METHODS
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On noncausal weighted least squares identification of nonstationary stochastic systems
PublicationIn this paper, we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted (windowed) least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts...
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Vapor correction of FTIR spectra – A simple automatic least squares approach
PublicationFTIR spectroscopy is one of the best techniques to study intermolecular interactions. However, such an application requires high quality spectra with as little noise as possible, which are often difficult to obtain. One of the main sources of unwanted interference is water vapor. Here a robust method is proposed for automatic, fast and reliable vapor correction of FTIR spectra. The presented least squares approach of vapor subtraction...
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Remarks on the convergence of an iterative method of solution of generalized least squares problem
PublicationW pracy przedstawiona jest metoda iteracyjna znajdowania regularyzowanego (w sensie Tichonowa) rozwiązania układu równań Ax=b z dowolną macierzą A. Dla danej liczby alfa i wektora g daje ona ciąg przybliżeń zbieżny do rozwiązania (w sensie najmniejszych kwadratów) tego układu. Rozwiązanie to minimalizuje odległość zbioru wszystkich rozwiązań średniokwadratowych układu Ax=b od wektora g. Podane zostało również oszacowanie szybkości...
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3D POINT-CLOUD SPATIAL EXPANSION BY TOTAL LEAST-SQUARES LINE FITTING
PublicationPoint-cloud spatial expansion (PCSE) allows the creation of a new pointcloud form that presents an alternative geometry of an entire object in a single spatial view. Spatial expansion facilitates the analysis process and introduces an additional spatial parameter describing the point cloud. An important element of the PCSE method is determining the position of the axis of symmetry of a symmetrical object: the procedure for determining...
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3d point-cloud spatial expansion by total least-squares line fitting
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Use of a Least Squares with Conditional Equations Method in Positioning a Tramway Track in the Gdansk Agglomeration
PublicationSatellite measurement techniques have been used for many years in different types of human activity, including work related to staking out and making use of rail infrastructure. First and foremost, satellite techniques are applied to determine the tramway track course and to analyse the changes of its position during its operation. This paper proposes using the least squares with conditional equations method, known in geodesy (LSce)....
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Use of a Least Squares with Conditional Equations Method in Positioning a Tramway Track in the Gdansk Agglomeration
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Application of the Least Squares Method to the approximation of equally spaced samples in frequency measurement approach
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Estimation and Prediction of Vertical Deformations of Random Surfaces, Applying the Total Least Squares Collocation Method
PublicationThis paper proposes a method for determining the vertical deformations treated as random fields. It is assumed that the monitored surfaces are subject not only to deterministic deformations, but also to random fluctuations. Furthermore, the existence of random noise coming from surface’s vibrations is also assumed. Such noise disturbs the deformation’s functional models. Surface monitoring with the use of the geodetic levelling...
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Application of least squares with conditional equations method for railway track inventory using GNSS observations
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Application of Least Squares with Conditional Equations Method for Railway Track Inventory Using GNSS Observations
PublicationSatellite geodetic networks are commonly used in surveying tasks, but they can also be used in mobile surveys. Mobile satellite surveys can be used for trackage inventory, diagnostics and design. The combination of modern technological solutions with the adaptation of research methods known in other fields of science offers an opportunity to acquire highly accurate solutions for railway track inventory. This article presents the...
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Least Squares Estimators of Peptide Species Concentrations Based on Gaussian Mixture Decompositions of Protein Mass Spectra
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Weighted least squares parameter estimation for model predictive control of integrated wastewater systems at medium time scale.
PublicationW artykule przedstawione zostało sformułowanie i implementacja algorytmu ważonej sumy najmniejszych kwadratów na przesuwnym oknie pomiarowym dla celów estymacji parametrów modelu typu szara skrzynka. Model typu szara skrzynka dynamiki reaktora biologicznego jest wykorzystywany przez moduł sterowania predykcyjnego sterujący zintegrowanym systemem ściekowym w średniej skali czasu. Algorytm estymacji parametrów był walidowany na symulatorze...
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KAMIŃSKI W.: Modelowanie przemieszczeń pionowych mieszaną, ortogonalną metodą najmniejszych kwadratów (Mixed Total Least Squares)
PublicationProblematyka modelowania przemieszczeń pionowych standardową metodą najmniejszych kwadratów i mieszaną ortogonalną metodą najmniejszych kwadratów. Przykłady praktycznych obliczeń na rzeczywistych i symulowanych wynikach obserwacji.
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Prediction of near-bottom water salinity in the Baltic Sea using Ordinary Least Squares and Geographically Weighted Regression models
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Interactions between hydration spheres of two different solutes in solution: The least squares fitting with constraints as a tool to determine water properties in ternary systems
PublicationBiological systems are complex and the problem of their description lies in mutual interactions between their components. This paper is focused on model experiment-based studies which can reduce these difficulties. The ternary aqueous N-methylacetamide (NMA)–Na2HPO4 system has been studied by means of the FTIR spectroscopy. A novel difference spectra method aimed to extract the spectral contribution of water affected simultaneously...
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Power Grid Frequency Estimation Based on Zero Crossing Technique Using Least Squares Method to Approximate Sampled Voltage Signal Around Zero Level
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Power grid frequency measurement in LabVIEW environment using the least mean squares method to signal phase approximation in the presence of noise
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On ''cheap smoothing'' opportunities in identification of time-varying systems
PublicationIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate into the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Despite the possible performance improvements, the existing smoothing...
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Karhunen-Loeve-based approach to tracking of rapidly fading wireless communication channels
PublicationWhen parameters of wireless communication channels vary at a fast rate, simple estimation algorithms, such as weighted least squares (WLS) or least mean squares (LMS) algorithms, cannot estimate them with the accuracy needed to secure the reliable operation of the underlying communication systems. In cases like this, the local basis function (LBF) estimation technique can be used instead, significantly increasing the achievable...
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ADAPTIVE BACKSTEPPING TRACKING CONTROL FOR OVER-ACTUATED DP MARINE VESSEL WITH INERTIA UNCERTAINTIES
PublicationDesigning a tracking control system for an over-actuated dynamic positioning marine vessel in the case of insufficient information on environmental disturbances, hydrodynamic damping, Coriolis forces and vessel inertia characteristics is considered. The designed adaptive MIMO backstepping control law with control allocation is based on Lyapunov control theory for cascaded systems to guarantee stabilization of the marine vessel...
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Synthesis of coupled lossy resonator filters.
PublicationA technique for fast synthesis of coupling matrix low-pass prototypes of generalized. Chebyshev bandpass filters with lossy resonators is presented in this letter. The coupling matrix is found by solving a nonlinear least squares problem based on zeros and poles of filter's transfer functions.
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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublicationWhen identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...
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Optimal and suboptimal algorithms for identification of time-varying systems with randomly drifting parameters
PublicationNoncausal estimation algorithms, which involve smoothing, can be used for off-line identification of nonstationary systems. Since smoothingis based on both past and future data, it offers increased accuracy compared to causal (tracking) estimation schemes, incorporating past data only. It is shown that efficient smoothing variants of the popular exponentially weighted least squares and Kalman filter-based parameter trackers can...
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Waveform design for fast clutter cancellation in noise radars
PublicationCanceling clutter is an important, but computation-ally intensive part of signal processing in noise radars. It is shown that considerable improvements can be made to a simple least squares canceler if minor constraints are imposed onto noise waveform. The proposed scheme is potentially capable of canceling clutter in real-time, even for high sampling rates.
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On the synthesis of coupled-lossy resonator filters with unloaded quality factor control
PublicationA technique for fast synthesis of coupling matrix low-pass prototypes of generalized Chebyshev bandpass filters with lossy resonators is presented in this paper. The coupling matrix is found by solving a nonlinear least squares problem based on zeros and poles of filter's transfer functions. Additional constraints are introduced that allow one to control the level of unloaded quality factor of resonators.
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Modal parameters identification with Particle Swarm Optimization
PublicationThe paper presents method of the modal parameters identification based on the Particle Swarm Optimization (PSO) algorithm [1]. The basic PSO algorithm is modified in order to achieve fast convergence and low estimation error of identified parameters values. The procedure of identification as well as algorithm modifications are presented and some simple examples for the SISO systems are provided. Results are compared with the results...
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Fast clutter cancellation for noise radars via waveform design
PublicationCanceling clutter is an important, but very expensive part of signal processing in noise radars. It is shown that considerable improvements can be made to a simple least squares canceler if minor constraints are imposed onto noise waveform. Using a combination of FPGA and CPU, the proposed scheme is capable of canceling both stationary clutter and moving targets in real-time, even for high sampling rates.
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Mechanical properties of polyvinyl chloride-coated fabric under cyclic tests
PublicationThe aim of the present paper is to propose a method of laboratory tests necessary for the identification of mechanical properties of the coated fabric. The material parameters of the coated fabric AF 9032 are specified on the basis of the uniaxial and biaxial tensile tests. For the identification process, the techniques based on the least squares methods are used. Additionally, the uniaxial and biaxial cyclic tests are performed...
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Cheap Cancellation of Strong Echoes for Digital Passive and Noise Radars
PublicationThe problem of cancellation of strong, potentially nonstationary,echoes in noise radars and passive radars utilizing digitaltransmissions is considered. The proposed solution is a multi-stage procedure.Initial clutter estimates, obtained using the least mean squares(LMS) algorithm, are refined using specially designed filters, "matched"to spectral densities of targets and clutter. When the postprocessing filtersare noncausal, the...
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Intelligent monitoring the vertical dynamics of wheeled inspection vehicles
PublicationThe problem of intelligent monitoring of the vertical dynamics of wheeled inspection vehicles is addressed. With the independent MacPherson suspension system installed, the basic analysis focuses on the evaluation of the parameters of the so-called quarter car model. To identify a physically motivated continuous description, in practice, dedicated integral-horizontal filters are used. The obtained discrete model, which retains...
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Parameter and delay estimation of linear continuous-time systems
PublicationIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous identification...
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Parameter and delay estimation of linear continuous-time systems
PublicationIn this paper the problem of on-line identification of non-stationary delay systems is considered. Dynamics of supervised industrial processes is usually described by ordinary differential equations. Discrete-time mechanization of their continuous-time representations is based on dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures implemented in recursive forms are applied for simultaneous...
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On–line Parameter and Delay Estimation of Continuous–Time Dynamic Systems
PublicationThe problem of on-line identification of non-stationary delay systems is considered. The dynamics of supervised industrial processes are usually modeled by ordinary differential equations. Discrete-time mechanizations of continuous-time process models are implemented with the use of dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures mechanized in recursive forms are applied for simultaneous...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Resistant to correlated noise and outliers discrete identification of continuous non-linear non-stationary dynamic objects
PublicationIn this article, specific methods of parameter estimation were used to identify the coefficients of continuous models represented by linear and nonlinear differential equations. The necessary discrete-time approximation of the base model is achieved by appropriately tuned FIR linear integral filters. The resulting discrete descriptions, which retain the original continuous parameterization, can then be identified using the classical...
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Resistant to correlated noise and outliers discrete identification of continuous non-linear non-stationary dynamic objects
PublicationIn this study, dedicated methods of parameter estimation were used to identify the coefficients of continuous models represented by linear and nonlinear differential equations. The necessary discrete-time approximation of the base model is achieved by appropriately tuned FIR linear integral filters. The resulting discrete descriptions, which retain the original continuous parameterization, can then be identified using the classical...
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Liniowe i nieliniowe modele wielowymiarowej kalibracji do predykcji stężenia substancji z pomiarów woltamperometrycznych
PublicationPomiary woltamperometryczne znajdują zastosowanie w wielu dziedzinach nauki i techniki, np. w przemyśle farmaceutycznym. Dane uzyskane w wyniku takich pomiarów zawierają informację odnośnie rodzaju i stężenia badanej substancji, jednakże są one często kłopotliwe w bezpośredniej interpretacji. Z tego powodu, istnieje konieczność wykorzystania odpowiednich metod matematycznych, które umożliwiają uzyskanie bezpośredniej i precyzyjnej...
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Mechanical properties for preliminary design of structures made from PVC coated fabric
PublicationIn this paper, laboratory tests necessary for the identification of non-linear elastic immediate properties of the PVC coated polyester fabric (like AF 9032) are described. The material parameters are specified on the basis of the uniaxial tensile tests in the warp and weft directions as well as on the base of the biaxial tensile tests. For the identification process techniques based on the least squares method are used. The authors...
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Odbiór zbiorczy z filtracją adaptacyjną RLS w transmisji danych w kanale hydroakustycznym
PublicationTransmisja danych w kanale hydroakustycznych realizowana jest w trudnych warunkach propagacyjnych. Jednym z problemów podczas takiej transmisji są zakłócenia międzysymbolowe (ISI – intersymbol interference) spowodowane głównie przez efekt wielodrogowości. To zjawisko utrudnia, bądź uniemożliwia transmisję danych w takim kanale. Stąd podjęto analizę wpływu zastosowania odbioru zbiorczego oraz filtracji adaptacyjnej RLS (Recursive...
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A procedure for elastoplastic hardening function identification.
PublicationThe inverse analysis method for identifying a nonlinear hardening function,which governs a plastic yielding of soil and rock materials in the framework of elastoplastic theory is presented. A concept of two stage finite element based on spatial discretization of computational space and hardening function space is introduced. The proposed inverse analysis can be classified as the output least squares method. The Levenberg Marquard...
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Elimination of Impulsive Disturbances From Stereo Audio Recordings Using Vector Autoregressive Modeling and Variable-order Kalman Filtering
PublicationThis paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings. The proposed solution is based on vector autoregressive modeling of audio signals. Online tracking of signal model parameters is performed using the exponential ly weighted least squares algo- rithm. Detection of noise pulses an d model-based interpolation of the irrevocably distorted sampl es is realized using an adaptive, variable-order...
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Determination of time delay between ventricles contraction using impedance measurements
PublicationThe paper presents a novel approach to assessment of ventricular dyssynchrony basing on multichannel electrical impedance measurements. Using a proper placement of electrodes, the sensitivity approach allows estimating time difference between chambers contraction from over determined nonlinear system of equations. The theoretical considerations which include Finite Element Method simulations were verified using measurements on...
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On noncausal identification of nonstationary stochastic systems
PublicationIn this paper we consider the problem of noncausal identification of nonstationary,linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts its smoothing...
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Three solvers for MIMO noise radar clutter cancellation - a performance comparison
PublicationThe problem of canceling strong clutter echos in a MIMO noise radar is considered. Execution times of three algorithms is compared. The first solution is a standard Least Squares approach employing Cholesky decomposition of the transmitted signal sample autocorrelation matrix. The second approach is based on careful waveform design which guarantees that the signal sample autocorrelation matrix has Toeplitz structure. This enables...
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Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublicationAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state-of-the-art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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Impact of cross-section centers estimation on the accuracy of the Point cloud spatial expansion using robust M-estimation and Monte Carlo simulation
PublicationThe point cloud spatial expansion (PCSE) method creates an alternative form of representing the shape of symmetrical objects and introduces additional descriptive geometric parameters. An important element of the procedure is determining the course of the axis of symmetry of cylindrical objects based on cross-sections of point clouds. Outliers occurring in laser measurements are of great importance in this case. In this study,...
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Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm
PublicationThis paper analyses the effectiveness of determining gas concentrations by using a prototype WO3 resistive gas sensor together with fluctuation enhanced sensing. We have earlier demonstrated that this method can determine the composition of a gas mixture by using only a single sensor. In the present study, we apply Least-Squares Support-Vector-Machine-based (LS-SVM-based) nonlinear regression to determine the gas concentration...