The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper deals with the results on the reconstruction accuracy of the irregularly sampled discrete-time signal (DTS) with unknown sampling locations. Reconstruction is performed by means of special reconstruction algorithms based on the sampling locations estimation. Comparison is done for results of estimation of the algorithms accuracy and accuracy of signal reconstruction by means of interpolation...
The paper presents an approach for tracking a variable number of objects by using a multi-layer particle filter combined with an extended Expectation Maximization (EM) clustering. The approach works on basis of binary foreground images coming from previous background subtraction. The multi-layer particle filter is an improvement of a conventional particle filter approach. It uses an introduced adaptive...
In robotics, non-linear least squares estimation is a common technique for simultaneous localization and mapping. One of the remaining challenges are measurement outliers leading to inconsistency or even divergence within the optimization process. Recently, several approaches for robust state estimation dealing with outliers inside the optimization back-end were presented, but all of them include...
This paper formulates and studies the problem of distributed filtering based on randomized gossip strategy in order to estimate the state of a dynamic system via all sensors in a network. First we introduce the randomized gossip algorithm by which the fastest averaging strategy can be obtained for a network with an arbitrary topology. Then we combine the randomized gossip algorithm with the information...
In this paper, an Artificial Neural Network (ANN) is employed for the estimation of LaTeral Misalignment (LTM) as well as compensation of its effect on Dynamic Wireless Power Transfer (DWPT) systems for Electric Vehicles (EVs) charging. In a DWPT system, energy efficiency and energy transfer capability are significantly affected by the degree of LTM. Therefore, the real-time estimation of LTM, followed...
In recent years, the statistical inference and algorithm for the complex diffusion process of incomplete data have become a hot topic that scholars of probability and statisticians are concerned with and calls for further study. Based upon the all-directional, multi-angle random dynamic information flow research, this article expands the information flow research in the ordinary information space...
Evaluating driving performance of autonomous vehicles is as important as developing automated driving algorithms. In order to ensure passenger safety, evaluation of driving behavior is required before delivering autonomous vehicles to customers. An Interacting Multiple Model (IMM)-based driver evaluation algorithm was developed and it provides various information associated with multiple driving aggressiveness...
There are quite a few high dimensional time-series data co-ocurring each other such as lip motions, voices, and face appearances and so on. When capturing the correspondent relationships among those time-series data with different dimensionality, we need to make the dimensionality all the same size so that they can be compared each other. To achieve this, Gaussian Process Latent Variable Models (GPLVM)...
The paper describes and compares some approaches to the use of measurement results for control using the classical feedback principle. The application of a linear control law based on the state vector estimates obtained with the use of the Kalman filter and the minimax filter is described. There are methods for control quality improving by means of the preliminary processing of measurements and another...
The ambiguity search space has a great effect on integer ambiguity searching efficiency and confirmation. In the case of high ambiguity dimension, the search space is determined when the ambiguity dimension is large. The conventional method is prone to the ambiguity fixed failure. And the actual ambiguity group number and the expected value of a large deviation by the conservative method, resulting...
This paper studies the distributed coordinated tracking problem for multiple Euler-Lagrange systems (MELSs) with full-state constraints. Firstly, a distributed finite-time sliding-mode estimator (DFSE) is introduced to access precise estimations of the leader's position and velocity. Then, to guarantee the full-state constraints of MELSs, we use the barrier Lyapunov function (BLF) technique and a...
In this paper a systematic model based approach to state estimation for Permanent Magnet Synchronous Motor (PMSM) to built up sensorless drives is presented. A moving horizon estimation (MHE) algorithm is used, an optimization based scheme that yields excellent performance. Under mild assumptions, an optimal problem of type Equality Constrained Quadratic Programming (EQP) is resolved at each iteration...
A Bayesian approach for system identification using kernel functions is a popular method. The kernel functions are considered as certain prior knowledge about a target system, so selecting proper kernels is required. Recent studies show that it is successful to use OBF-s(orthonormal basis function)-based kernels as the kernel functions, but estimating hyper-parameters of the kernel functions is a...
An auto-tuning and self-adaptation procedure for high-frequency injection (HFI) based position and speed estimation algorithms in IPMSM and SynRM drives is proposed in this paper. Analytical developments show that the dynamics of the high-frequency tracking loop varies with differential inductances, which in turn depend on the machine operating point due to saturation. On-line estimation and adaptation...
In a passive radio-frequency identification (RFID) system the reader communicates with the tags using the EPC Global UHF Class 1 Generation 2 protocol with dynamic frameslotted ALOHA. Due to the unique challenges presented by a low-power, random link, the channel efficiency of even the most modern passive RFID system is less than 40%. Hence, a variety of methods have been proposed to estimate the...
The paper considers the problem of increasing the speed of monochrome multitone image (MMI) approximation, which consists in replacement of original palette with palette that has less number of tones. Often, for solving such a problem, the heuristic optimization-search algorithms are used. Their drawback is that, they cannot guarantee to find the solution for the given optimization criteria, which...
The objective of this work is to evaluate performance of three phasor estimation algorithms proposed in literature, under electrical system signals. Signals obtained from electrical systems response to disturbances in which the electrical system is stable or operates in a condition of transient instability, frequency or voltage. The performance during the transient state of the system is evaluated...
Glottal closure instant (GCI) is an important feature in many speech processing applications. Many algorithms have been proposed for GCI estimation from speech signals. The objective of the proposed work is to provide a comprehensive analysis of the performance of various GCI estimation algorithms for singing voice in Indian context. GCI estimation algorithms such as Dynamic Programming Phase Slope...
In context of manufacturing, numerous models are designed to appropriately represent the facility layout problem (FLP) and a variety of optimization methods have been applied to solve these models. The ultimate goal of these methods is to find optimal solutions, In regard to Swarm Intelligence (SI), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) are regarded as the most important...
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...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.