Wyszukiwarka
Filtry
wszystkich: 1610
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: LEAST SQUARES ESTIMATION
-
Parameter and delay estimation of linear continuous-time systems
PublikacjaIn 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...
-
Parameter and delay estimation of linear continuous-time systems
PublikacjaIn 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...
-
A simplified channel estimation procedure for NB-IoT downlink
PublikacjaThis paper presents a low-complexity channel estimation procedure which is suitable for use in energy-efficient NB-IoT user equipment devices. The procedure is based on the well-established least squares scheme, followed by linear interpolation in the time domain and averaging in the frequency domain. The quality of channel estimation vs. signal-to-noise ratio is evaluated for two channel models and compared with the performance...
-
Impact of cross-section centers estimation on the accuracy of the Point cloud spatial expansion using robust M-estimation and Monte Carlo simulation
PublikacjaThe 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,...
-
On–line Parameter and Delay Estimation of Continuous–Time Dynamic Systems
PublikacjaThe 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...
-
On ''cheap smoothing'' opportunities in identification of time-varying systems
PublikacjaIn 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...
-
Karhunen-Loeve-based approach to tracking of rapidly fading wireless communication channels
PublikacjaWhen 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...
-
On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublikacjaWhen 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...
-
Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublikacjaThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
-
Optimal and suboptimal algorithms for identification of time-varying systems with randomly drifting parameters
PublikacjaNoncausal 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...
-
Identification of models and signals robust to occasional outliers
PublikacjaIn 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,...
-
Identification of models and signals robust to occasional outliers
PublikacjaIn 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,...
-
Estimation of DC motor parameters using a simple CMOS camera
PublikacjaDifferent components of control systems for mobile robots are based on dynamic models. In low-cost solutions such a robot is wheeled and equipped with DC motors, which have to be included in the model of the robot. The model is fairly simple but determination of its parameters needs not to be easy. For instance, DC motor parameters are typically identified indirectly using suitable measurements, concerning engine voltage, current,...
-
Estimation of the amplitude of the signal for the active optical gesture sensor with sparse detectors
PublikacjaIn this paper we deal with the problem of precise gesture recognition for the active optical proximity sensor with sparse 8 photodiodes. We particularly focus on developing the method of estimating the real, usually not observable, maximum signal value representing maximum intensity of light reflected from an obstacle present in the front of the sensor. Different configurations of the fingers were used as an obstacle. The Monte Carlo...
-
Marek Zienkiewicz dr inż.
OsobyDoktor inżynier Marek Hubert dwojga imion Zienkiewicz jest absolwentem Wydziału Geodezji, Inżynierii Przestrzennej i Budownictwa Uniwersytetu Warmińsko-Mazurskiego w Olsztynie. Zainteresowania naukowe w okresie studiów inżynierskich, magisterskich i doktoranckich rozwijał pod opieką przedstawicieli olsztyńskiej szkoły geodezyjnego rachunku wyrównawczego. W roku 2011 uzyskał tytuł zawodowy magistra inżyniera w zakresie geodezji...
-
Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublikacjaAccurate 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...
-
A Universal Gains Selection Method for Speed Observers of Induction Machine
PublikacjaProperties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response...
-
Modal parameters identification with Particle Swarm Optimization
PublikacjaThe 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...
-
Optimally regularized local basis function approach to identification of time-varying systems
PublikacjaAccurate 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...
-
On noncausal identification of nonstationary stochastic systems
PublikacjaIn 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...