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SEIR (Susceptible-Exposed-Infected-Recovered) is a general and widely-used diffusion model that can model the diffusion in different contexts such as idea spreading and disease propagation. Here, we tackle the problem of inferring graph edges if we can only observe a SEIR diffusion process spreading over the nodes of a graph. This problem is of importance in the common case where node states can be...
When establishing object correspondence across non-overlapping cameras, the existing methods combine separate likelihoods of appearance and kinematic features in a Bayesian framework, constructing a joint likelihood to compute the probability of re-detection. A drawback of these methods is not having a proper approach to reduce the search space when localizing an object in a subsequent camera once...
A new approach to identification of Wiener models by using the least-squares method is presented. It is assumed that an inverse characteristic of the nonlinear element can be expanded to the power series of a finite and known order. A modified definition of the identification error is proposed and parameters of a modified serial-parallel Wiener model are estimated. A simulation example is included...
In this contribution we discuss some variance properties of a two-step ARX estimation scheme. An expression for the co-variance of the final low order model is calculated and it is discussed how one should minimize this covariance. The implication of the results is that identification of the dynamics of a system could very easily be performed with standard linear least squares (two times), even if...
H∞ identification of model sets for linear, time-invariant, discrete-time, BIBO stable SISO systems is here considered, assuming a known bound on the transfer-function derivative magnitude as prior information on the system to be identified. Experimental information consists of a finite number of measurements in the frequency domain, corrupted by a pointwise bounded additive noise. The aim is to deliver...
In this paper, an attractive and novel algorithm for improving irreducible model identification of continuous time(CT) MIMO systems has been presented. The algorithm is based on least — squares (LS) estimates of Markov parameters (MP) using input output data and residual whitening. By choosing a linear-in-parameters model structure, the estimation becomes linear and asymptotically robust to zero-mean...
We give a short review on Bayesian techniques for neural networks and demonstrate the advantages of the approach in a number of industrial applications. Bayesian approach provides a principled way to handle the problem of overfitting, by averaging over all model complexities weighted by their posterior probability given the data sample. The approach also facilitates estimation of the confidence intervals...
A key issue in system identification is how to cope with high system complexity. In this contribution we stress the importance of taking the application into account in order to cope with this issue. We define the concept “cost of complexity” which is a measure of the minimum required experimental effort (e.g. used input energy) as a function of the system complexity, the noise properties, and the...
The turtle retina is organized with predominantly two important classes of cells. The first, known as A cells, is sensitive only to light intensity. The other, known as B cells, is also sensitive to direction of targets. We propose models for both types of cells and demonstrate results the models yield. We also show the encoding properties of a single cells and show how a single B-cell can be used...
H∞ identification of model sets for LTI discrete-time exponentially stable SISO systems, from noise corrupted measurements in the time and/or the frequency domain, is considered. The assumptions on the noise can account for information on its maximal magnitude and deterministic uncorrelation properties. Identification of optimal model sets requires the computation of the Chebicheff center in a weighted...
The effects of a controller on the residual wavefront variance in an adaptive optics system can be represented by a discrete-time system. Consequently, the controller design is optimized by the solution of a discrete-time Linear-Quadratic-Gaussian (LQG) problem. The purpose of this paper is to analyze the structure of the LQG controller that minimizes the residual wavefront variance. It is shown that...
Microcircuits in the visual cortex of freshwater turtles have been revisited. These consist of a model of the retina, the lateral geniculate nucleus (LGN) and the visual cortex. In this paper, we present, via simulation how visual input on the retina is subsequently processed by the LGN leading up to an input to the cortex that generates a wave of activity. To gain access to the information content...
Aims: This theoretical investigation aimed to increase the dynamic range of a pulse oximeter by reducing electronic noise in the photoplethysmogram (PPG) using characteristics of the heart rate (HR) signal. The PPG is used to measure blood oxygen saturation (SpO2).
This paper describes, a graphical user interface (GUI) for synthetic simulation of maternal-foetal ECG mixtures. The GUI is directly linked to the previously introduced fecgsyn ECG model, which was used for producing a subset of data of the Physionet/Computing in Cardiology Challenge 2013. fecgsyngui serves as a tool that facilitates the use of the broad capabilities of fecgsyn.
Anatomical structure labeling in echocardiogram images will assist cardiac disease diagnosis by providing a framework for doing geometrical statistics. General labeling algorithms often focus on stationary body structures and do not perform well in echocardiography due to cardiac motion, low signal to noise ratio, and structural deformation caused by diseases. In this paper, we propose a new method...
Ocean ambient noise level is a function of time, frequency and location. The noise level at different frequency ranges and time spans are contributed by different sources of ambient noise. At low frequencies below 1 kHz, sites near ocean shipping lanes are noisier than other open-ocean locations. Generally, in the range 1 – 50 kHz, sea state dependent noise is dominant. When rain is present, the rain-generated...
Accurate fingerprint orientation is a prerequisite in fingerprint based recognition system. This paper proposes an algorithm for modeling the fingerprint orientation field by using a model based algorithm based on the weighted Legendre basis. Weights required in the modeling are obtained by using symmetric filters, such that: i) high weights should be assigned to the areas near singular points, ii)...
Target tracking is one of the most important applications for wireless sensor networks (WSNs). It is usually assumed that the knowledge of the sensor nodes' position is known precisely. However, practically nodes are randomly deployed without prior knowledge about their own positions. In this situation, simultaneous localization and tracking (SLAT) is necessary and is receiving more and more research...
We present a digital watermarking algorithm for 3D model which is based on encrypted holographic digital watermarking algorithm to protect the embedded watermark information (such as a specific identity of the copyright information, etc.) and to improve the security and robustness of the digital watermark information. Firstly, the watermark image is processed by the double random phase modulation...
This paper introduces improvements to estimate 3D object pose from point clouds. We use point-pair feature for matching instead of traditional approaches using local feature descriptors. In order to obtain high accuracy estimation, a discriminative descriptor is introduced for point-pair features. The object model is a set of point pair descriptors computed from CAD model. The voting process is performed...
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