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Joint detection of asynchronous signal streams via iterative reception is investigated. While basic theoretical system performance is well understood, practical aspects such as those arising from time-varying channels due to parameter drifts are less well explored. The integration of adaptive estimators for these time-varying channels for all data streams into the iterative receiver processor is investigated...
A problem of frequency identification for a biased sinusoidal signal is considered. An identification algorithm is proposed which ensures exponential convergence for a case of an input signal with no noise and additionally allows to estimate an amplitude and a bias of the input signal. For a case of a noised input signal an adaptive cascade of band-pass filters is proposed coupled with the proposed...
In this paper, we study the received signal strength (RSS) based localization problem with correlated shadowing between pairs of RSS measurements. By linearizing the correlated RSS model, a weighted least squares (WLS) is formulated to obtain the target location. We also study the correlated shadowing when differential received signal strength (DRSS) is deployed as measurements. Numerical simulations...
This paper proposes a fault detection methodology for incipient faults that combines different residual generation methods (observers and l-step ahead predictors) with different convergence velocity to the real output trying to benefit from the advantages offered by each one. The integration is based on generating a timed automaton, which combines the information extracted from each method in order...
Side-channel analysis of cryptographic systems can allow for the recovery of secret information by an adversary even where the underlying algorithms have been shown to be provably secure. This is achieved by exploiting the unintentional leakages inherent in the underlying implementation of the algorithm in software or hardware. Within this field of research, a class of attacks known as profiling attacks,...
Real data often are comprised of multiple modalities or different views, which provide complementary and consensus information to each other. Exploring those information is important for the multi-view data clustering and classification. Multiview embedding is an effective method for multiple view data which uncovers the common latent structure shared by different views. Previous studies assumed that...
In this paper, tracking problem is considered as a sparse approximation of target by templates created during video process. In addition, some trivial templates are used to avoid the effects of noise and illumination changes. Each candidate is sparsely represented by the template set. This goal is achieved by solving an l1- regularized least-square equation. To find tracking result, a candidate with...
Photoplethysmography (PPG) can be carried out through facial video recording by a smart phone camera in ambient light. The main challenge is to eliminate motion artifacts and ambient noise. We describe a real-time algorithm to quantify the heart beat rate from facial video recording captured by the camera of a smart phone. We extract the green channel from the video. Then we normalize it and use a...
In this paper, we propose a practical and accurate SOC (State of Charge) estimation system for Lithium- ion battery. The algorithm of SOC estimation uses the Extended Kalman filter, and estimates the SOC using OCV-SOC Curve, internal impedance, and the external current and voltage of a battery.12288; It is constructed on a discrete-time system model of battery model using numerical analysis method,...
Image segmentation is an important task in computer vision. The task of image segmentation is to portion image into segments, thus provide more meaningful information of the image contents. Many methods have been developed for numerous application. The common problems of most of the segmentation techniques are scattered segmentation lines, too much details, small or thin segments, and noisy segmentation...
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...
This paper proposes a reduction method of stochastic disturbance that is focused on haptic information in the micro space. Presently in the industry, haptic information is attracting attention as the tertiary media following audio and visual information. Haptic information has characteristics of bidirectionality and scaling that extended human ability by using master and slave robots. Especially,...
Microcantilever based sensors are very promising devices for biochemical applications. They usually operate in two modes. In the first one a microcantilever static bending induced by the surface stress is observed, while in the second mode, resonant frequency shift caused by mass loading is measured. In the paper, the real-time noise analysis (RTNA) technique is presented. It is based on ARMA process...
One of the most profound use of ultrasound imaging is to generate the image of fetal during pregnancy. This paper will describe an ellipse detection approach to automatically detect and approximate the head size of the fetal. The method was developed using the Hough Transform techniques that have been modified and optimized by Particle Swarm Optimization (PSO). Experiments of the method are tested...
In this paper, the problem of target detection in the clutter plus Gaussian noise background is considered. The published detectors group the clutter and the noise as a single parameter; differently, we deal separately with the clutter and the noise. In the paper, the noise is assumed to be obtained in advance and the clutter is distributed according to a certain distribution. An adaptive target detector...
Accurate estimation of the amplitude parameter of sinusoidal signals from noisy observations is an important problem in many signal processing applications. In this paper, the problem is investigated under the assumption of non-Gaussian noise of Alpha stable distribution. According to the chaos theory and the properties of almost periodic functions, a new estimation method for amplitude of sinusoidal...
The classic Kalman theory is established on time continuous observation. Using on the spatial-temporal duality, Spatial Kalman Filters (SKF) is introduced based on spatial continuity. Further, an improved SKF named Spatial-Temporal Kalman Filters (STKF), which is based on time and spatial distribution, is proposed. It is suitable for applications in open fields, such as multi-sensors information merging...
Polar transmitters suffer from the problem of having high out-of-band noise. To solve this problem, most of the proposed solutions rely on increasing the sampling rate of the phase branch. In this paper, we present a novel method based on processing the digital radius signal in order to reduce the out-of-band noise. The proposed method modifies the output of the Digital-to-Analog Converter (DAC) in...
Due to the Doppler sensitive effective in noise radar, we present a Doppler compensation algorithm based on conjugate noise group. Firstly, the Doppler frequency is estimated by the spectrum of mixed signal within the group. Then, the Doppler compensation function related to Doppler ambiguity is constructed. Finally, target detection is performed with the predetermined threshold in the two-dimensional...
This paper presents a new methodology to craft navigation functions for nonlinear systems with stochastic uncertainty. The method relies on the transformation of the Hamilton-Jacobi-Bellman (HJB) equation into a linear partial differential equation. This approach allows for optimality criteria to be incorporated into the navigation function, and generalizes several existing results in navigation functions...
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