This paper is concerned with the problem of finitehorizon energy-to-peak state estimation for a class of networked linear time-varying *** to the inherent vulnerability of network-based communication,the measurement s...
详细信息
This paper is concerned with the problem of finitehorizon energy-to-peak state estimation for a class of networked linear time-varying *** to the inherent vulnerability of network-based communication,the measurement signals transmitted over a communication network might be intercepted by potential *** avoid information leakage,by resorting to an artificial-noise-assisted method,we develop a novel encryption-decryption scheme to ensure that the transmitted signal is composed of the raw measurement and an artificial-noise term.A special evaluation index named secrecy capacity is employed to assess the information security of signal transmissions under the developed encryption-decryption *** purpose of the addressed problem is to design an encryptiondecryption scheme and a state estimator such that:1)the desired secrecy capacity is ensured;and 2)the required finite-horizon–l_(2)-l_(∞)performance is *** conditions are established on the existence of the encryption-decryption mechanism and the finite-horizon state ***,simulation results are proposed to show the effectiveness of our proposed encryption-decryption-based state estimation scheme.
We consider a perimeter defense problem in a planar conical environment comprising a turret that has a finite range and non-zero startup time. The turret seeks to defend a concentric perimeter against N ≥ 2 intruders...
We consider a perimeter defense problem in a planar conical environment comprising a turret that has a finite range and non-zero startup time. The turret seeks to defend a concentric perimeter against N ≥ 2 intruders. Upon release, each intruder moves radially towards the perimeter with a fixed speed. To capture an intruder, the turret's angle must be aligned with that of the intruder's angle and must spend a specified startup time at that orientation. We address offline and online versions of this optimization problem. Specifically, in the offline version, we establish that in general parameter regimes, this problem is equivalent to solving a Travelling Repairperson Problem with Time Windows (TRP-TW). We then identify specific parameter regimes in which there is a polynomial time algorithm that maximizes the number of intruders captured. In the online version, we present a competitive analysis technique in which we establish a fundamental guarantee on the existence of at best (N – 1)-competitive algorithms. We also design two online algorithms that are provably 1 and 2-competitive in specific parameter regimes.
In this paper, we provide a novel contraction-theoretic approach to analyze two-time scale systems, including those commonly encountered in Online Feedback Optimization (OFO). Our framework endows these systems with s...
详细信息
Cardiac ischemia, a prevalent cause of heart failure, remains the leading cause of death in Iran. Early diagnosis of this condition is crucial, and electrocardiogram (ECG) signal processing techniques offer valuable i...
详细信息
ISBN:
(数字)9798331529710
ISBN:
(纸本)9798331529727
Cardiac ischemia, a prevalent cause of heart failure, remains the leading cause of death in Iran. Early diagnosis of this condition is crucial, and electrocardiogram (ECG) signal processing techniques offer valuable insights. By analyzing ECG signals from ischemic patients and comparing them to those of normal individuals, we can extract relevant features for classification. Our study extracted some features from ECG signals, including statistical, time-based, frequency, and time-frequency features. We employed the self-organizing maps method (SOM) to identify the most informative features. Subsequently, we evaluated the classification accuracy using several machine learning algorithms, including support vector machines (SVM), Naive Bayes, Linear Discriminant Analysis (LDA), and Logistic Regression. The results demonstrated the superiority of the SOM method in selecting the best features compared to PCA, with accuracies of $\mathbf{9 1. 2 \%}, \mathbf{8 4. 3 \%}, \mathbf{7 2. 5 \%}$, and $88.9 \%$ for SVM, LDA, NB, and LR methods, respectively. Our findings contribute to the early detection and management of cardiac ischemia, potentially improving patient outcomes.
This study addresses the classic control problem of stabilizing an inverted pendulum on a moving cart, a challenge in control theory and robotics due to its inherent instability and highly nonlinear dynamics. We explo...
详细信息
ISBN:
(数字)9798350373073
ISBN:
(纸本)9798350373080
This study addresses the classic control problem of stabilizing an inverted pendulum on a moving cart, a challenge in control theory and robotics due to its inherent instability and highly nonlinear dynamics. We explore the application of Q-learning, a model-free reinforcement learning algorithm, and its efficacy in deriving an optimal control policy for the system without precise system models. Our approach utilizes Q-learning's capacity for stabilizing a pendulum in an upright position on the top of the horizontally moving cart within a certain boundary. Our strategy adapts to a dynamic environment while showcasing its robustness in developing control policies for complex systems. This research bridges classical control theory with reinforcement learning techniques, contributing to the domain by demonstrating the versatility and potential of machine learning in control tasks.
This paper presents a control structure featuring an operator $Q$ driven by the residual signal, which indicates the difference between the measurement output and the estimated output from an observer. The form of t...
详细信息
ISBN:
(数字)9798350356618
ISBN:
(纸本)9798350356625
This paper presents a control structure featuring an operator
$Q$
driven by the residual signal, which indicates the difference between the measurement output and the estimated output from an observer. The form of this observer is very general, as long as it can generate the estimated state or relevant information that will be incorporated into this control structure. The operator
$Q$
introduces an extra design freedom to address uncertainties, such that linear active disturbance rejection control (LADRC) can be interpreted as a special case in the Q-structure when a linear extended state observer is used.
Power electronic systems present a non-linear behavior mainly due to their switching nature. This is often combined with their interaction with non-linear systems, such as other switching converters, diode rectifiers,...
详细信息
With the development of science and technology,graph convolutional network has made great progress in improving the accuracy of action ***,there still exists some deficiencies in current ***,the human skeleton point c...
详细信息
ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
With the development of science and technology,graph convolutional network has made great progress in improving the accuracy of action ***,there still exists some deficiencies in current ***,the human skeleton point coordinates entering into the network are barely refined,which may cause large ***,the second-order information(the length and direction of bones),which can reflect action characteristics discriminatively,is rarely *** solve the above issues,a two stream graph convolutional network with pose refinement for skeleton based action recognition is ***,we use an adaptive block to to help improve the *** test our method on Kinetics dataset and the experiment show it can get better results than some recent methods,which plays a positive role in future research.
In data mining, frequent-pattern mining methods are used for handling binary databases. Utility mining addresses this limitation by considering the item utilities and quantities when discovering the high utility items...
详细信息
作者：
Shang, JunZhang, HanwenZhou, JingChen, TongwenTongji University
Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing
Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta
Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada
This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measureme...
暂无评论