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In this paper, an algorithm is developed for the identification of a Hammerstein system in the presence of non-stationary measurement noise in the form of an Auto Regressive Integral Moving Average (ARIMA) model. Many systems used in the chemical process control industry can be modelled with the Hammerstein structure, a block oriented model consisting of a memoryless non-linearity followed by a linear...
In this paper are presented some preliminary results on an autonomous lift subsystem made with the interconnection of a DC/AC controlled converter, a salient permanent magnet synchronous motor (SPMSM), the charge and counterweight and the mechanical transmission system. These results are firstly the derivation of a Bond Graph and a related Port-Controlled Hamiltonian (PCH) models and, secondly, the...
In this paper, a linear unbiased minimum-variance filtering problem is considered for a class of systems with randomly multi-step sensor delays. A new mathematical model is established for the multi-step sensor delays. Different from the augmented method for dealing with delayed systems, a linear unbiased minimum-variance filter design method is proposed without augmenting the state vector, which...
The hybrid emulator is a mixed-mode electronic circuit which mimics the characteristics of a real device on its terminals. This paper describes a novel approach to the modeling and emulation of general memristive, memcapacitive, and meminductive systems based on digital signal processing. A microcontroller measures the independent port quantity (voltage or current), computes the response, and sets...
The provision of reliable location estimates in WiFi fingerprinting localization is challenging, mainly because users typically carry heterogeneous devices that report Received Signal Strength (RSS) measurements from surrounding Access Points (AP) very differently. This may render the user-carried device incompatible with the fingerprinting system, in case the RSS radiomap was collected with a different...
This paper presents the methods for data processing technology of 3D points cloud with large unorganized and noisy point sets. Firstly, the noise points will be selected and deleted by the boundary points detection algorithm (BPDA). Secondly, we parameterize the interior points to the sphere model, the octahedron model and the geometry image model. Lastly, we give the error measure of the parameterization...
In this paper, we propose a new method for designing the variation restoration model which uses the noise evaluation to decide the approximation term and the information of geometrical structures in the blurred and noised images to choose the regularization term. We adjust the measurement for the approximation term based on the noise variance in the degraded image. By computing the mean curvature...
We present a grid-based 3D reconstruction method which integrates all costs given by stereo vision into what we call a Cost-Curve Occupancy Grid (CCOG). Occupancy probabilities of grid cells are estimated in a Bayesian formulation, from the likelihood of stereo cost measurements taken at all distance hypotheses. This is accomplished with only a small set of probabilistic assumptions which we discuss...
Co-location of frequency hopping systems occurs both in civilian and military applications. For close co-location in such scenarios, out-of-band emissions can be of significant importance and therefore have to be considered in the analysis. Intersystem-interference analysis of scenarios with several systems using a large amount of frequencies can be complex and time consuming if one wishes to consider...
An adaptive parameter estimation algorithm in the Laplace Transform domain is presented. It can be used to estimate transmission network Electromagnetic Transient equivalents from fault records. The algorithm is applied in modeling exponentially decaying DC offset of recorded fault currents. This information is of great importance in determining fault levels, in protection system design as well as...
As the need of highly secure data transmission in wireless communication has increased rapidly, physical layer security gains a lots of attention recently. The transmission of confidential data between two legitimate users in the existence of the passive eavesdropper with quasi-static Rayleigh channel is considered. A new technique is proposed in which a friendly noise is incorporated with confidential...
Pose graph optimization is an elegant and efficient formulation for robot localization and mapping. Experimental evidence suggests that, in real problems, the set of measurements used to estimate robot poses is prone to contain outliers, due to perceptual aliasing and incorrect data association. While several related works deal with the rejection of outliers during pose estimation, the goal of this...
Motion detection is of paramount importance in video surveillance systems. In this paper, a novel algorithm is proposed to extract the exact boundaries of moving objects in video frames. Using the concepts of Cross-Correlation and Edge Detection, we combine two well-known motion detection methods to extract the moving regions more accurately. Also, we modify these two methods in terms of accuracy...
The segmentation of brain magnetic resonance (MR) images into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) has been an intensive studied area in the medical image analysis community. The Gaussian mixture model (GMM) is one of the most commonly used model to represent the intensity of different tissue types. However, as a histogram-based model, the spatial relationship between...
Speckle noise is problematic in optical coherence tomography (OCT) and often obscures the structure details. In this paper, we propose a new method to reduce speckle noise from multiply scanned OCT slices. The proposed method registers the OCT scans using a global alignment followed by a local alignment based on global and local motion estimation. Then low rank matrix completion using bilateral random...
Background subtraction is one of important fundamental steps in many image processing applications such as object recognition, detection, tracking, human behavior analysis in video surveillance systems, etc. So the background subtraction method must be efficiency, that is saving time and space and have a good performance. In order to achieve this aim, a new background subtraction method is proposed...
As the golden standard in robust estimation, the classic RANSAC approach has undergone extensive research that contributed to further enhancements in run-time performance, robustness, and multi-structure support to name a few. Yet, the accelerating growth of multi-modal co-registered datasets requires a new adaptation of the RANSAC algorithm. In this paper, we propose a multi-modal fault-tolerant...
As one of the most important image segmentation models, the Mumford-Shah functional was developed to pursue a piecewise smooth approximation of a given image based on the regularization on the total length of curves. In this paper, we modify the Mumford-Shah model using Euler's elastic a as the regularization. A two-stage segmentation method is applied the Euler's elastic a regularized Mumford-Shah...
This paper describes a new technique of 2D projection transformation invariant template matching, GPT (Global Projection Transformation) correlation, as a natural extension of our earlier work on the affine-invariant GAT (Global Affine Transformation) correlation method. The key ideas are threefold. First, we show that arbitrary 2D projection transformation (PT) can be decomposed into a product of...
This paper presents a new video surveillance system called KVSS using background based on Type-2 Fuzzy Gaussian Mixture Models (T2 FGMMs). These techniques are used for resolving some limitations on Gaussian Mixture Models (GMMs) techniques on critical situations like moved camera jitter, illumination changes and objects being introduced or removed from the scene. In this context, we introduce descriptions...
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