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The paper deals with the state feedback quadratic mean square stabilization problem for multiple-input discrete-time networked control systems with quantization errors and multiplicative random noises. An analytic solvability condition is first derived for the single-input case in terms of the Mahler measure of the system and the effective worst signal-to-noise ratio (EWSNR) of the channel. Moreover,...
This paper is concerned with the verification of convexity for a class of stochastic control problems. In our previous work we proposed a hybrid method for solving the stochastic control problem with uncertainty in both the system and the constraint parameters. Under certain conditions, the optimization program is convex resulting in a drastic reduction in computational complexity over other methods...
This paper presents a novel sampling-based planner which guarantees robustness for linear systems subject to bounded process noise, localization error, and/or uncertain environmental constraints. The proposed algorithm extends RRT*, efficiently generating and optimizing robust, dynamically feasible trajectories. During planning, state constraints are individually tightened for robustness against future...
Successive interference cancellation (SIC) has been extensively applied to estimate transmit signals in communication systems. When the channel state information (CSI) and noise statistics are imperfectly estimated, the standard SIC estimators that ignore the model mismatch may perform poorly. This paper introduces regularized SIC estimation to provide robustness against the model mismatch. Suboptimal,...
In this paper, we consider the distributed consensus of high-dimensional first-order agents with relative-state-dependent measurement noises. Each agent can measure or receive its neighbors' state information with random noises, whose intensity is a nonlinear vector function of agents' relative states. For this kind of multi-agent networks, it is a prominent feature that the dynamics associated with...
This paper considers the problem of planning a path for an autonomous vehicle from a start to a goal location in presence of sensor intermittency modeled as a stochastic process, in addition to process and measurement noise. The aim is to plan a path that minimizes the localizational uncertainty for the vehicle upon arriving at the goal location. The main contribution of this paper is two-fold. We...
This paper considers the problem of motion planning for linear systems subject to Gaussian motion noise and proposes a risk-aware planning algorithm: CC-RRT∗-D. The proposed CC-RRT∗-D employs the chance-constraint approximation and leverages the asymptotically optimal property of RRT∗ framework to compute risk-aware and asymptotically optimal trajectories. By explicitly considering the state dependence...
This paper proposes a novel method to estimate relative poses for a calibrated stereo camera. Three corresponding points in 3D space are theoretically required to recover unconstraint motion which has six degrees of freedom. The proposed method solves this problem with only two 3D points by exploiting a common reference direction between poses. Two points are selected in accordance with the distance...
Underwater acoustic measurements are made to provide validation and qualification for a wide range of applications and developments in the off-shore industry, oceanography, defense, fisheries, and geophysics. However, measurements are only meaningful if they are performed in a technically sound manner and if they can be related to common standards of measurement. In this paper, a summary is given...
Time-of-flight (Tof) range imaging is a new suitable choice for measurement and modeling in many different applications such as robotics, machine vision, medical imaging, multimedia and so forth. But due to the technology's relatively new appearance on the market the knowledge of its capabilities is very low. This paper presents an uncertainty analysis for optical Tof sensors based on a four-phase-shift...
The paper describes an approach for semi-symbolic analysis of mixed-signal systems that contain discontinuous functions, e.g. due to modeling comparators. For modeling and semi-symbolic simulation, we use extended Affine Arithmetic. Affine Arithmetic is currently limited to accurate analysis of linear functions and mild non-linear functions, but not yet discontinuities. In this paper we extend the...
In this paper, a case study on the merit of adding the LISN for radiated-emission (RE) testing is demonstrated. For this study, a site source is created and considered as the device under test. This site source, activated by AC power, can generate harmonic reference signals ranging from 30 MHz to 1 GHz. The site source is then measured for numerous times. A large variation among these measurements...
Tracking or more generally state estimation of dynamic systems are tasks that appear in many different contexts - for instance in surveillance with wireless sensor networks. Usually the state-evolution equations are assumed to be known excepting some parameters. In this case, particle filters and related approaches have been applied with great success. Very few attempts, however, have been made so...
The support vector machine (SVM) has a good generalization performance, but the classification result of the SVM in some real problems is often unsatisfied. Because SVM is sensitive to the noisy data and it may not be effective under the high level of noise. To improve the performance of SVM in the noisy environment, we propose an ensemble learning model to address the noise problem in this work....
In this study interval type-2 fuzzy systems with non-singleton type-2 fuzzifire are used for identification and modeling nonlinear systems having noise with changing domain for fault detection purpose. The main idea in this fault detection method is to serve an upper bound and a lower bound as a confidence bound for system output that obtained from the interval type-2 fuzzy system. If we haven't precise...
The traditional triangulation algorithms in multiview geometry problems have the drawback that its solution is locally optimal. Robust Optimization is a specific and relatively novel methodology for handling optimization problems with uncertain data. The key idea of robust optimization is to find the best possible performance in the worst case. In this paper, we propose a novel approach which solves...
In recent years, targeted therapy to treat cancer is gaining popularity. However, how to quantitatively and dynamically analyze the drug effect for molecularly targeted agents is quite different from traditional cytotoxic drugs. A novel preclinical model combining experimental methods and theoretical analysis is proposed to investigate the mechanisms of action and identify pharmacodynamic characteristic...
In cognitive radio networks, unused frequency detection plays a crucial role in the discovery of spectrum opportunities for secondary systems (or unlicensed systems). The performance of unused spectra is characterized by both accuracy and efficiency. Currently, significant research effort has been made on improving the sensing accuracy. Several efficient techniques include energy detectors, feature...
In cognitive radio, the spectrum sensing plays a key role in determining the performance of both the primary and the secondary networks. The eigenvalue based detection (EbD) algorithm has received broad attentions, since it shows significant robustness to the noise uncertainty problem. However, in EbD algorithm, it is quite difficult to obtain the distribution for the eigenvalues of the statistic...
Wireless location has now gained considerable attention. One of the main problems facing accurate location in wireless communication systems is non-line-of-sight (NLOS) propagation. There are parametric and non-parametric methods to cope with NLOS errors. Compared with the parametric method, the non-parametric method can provide a unified solution with an optimal performance for different channel...
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