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In this paper, the robust adaptive control is proposed for a class of parametric uncertain nonlinear system with asymmetric non-smooth input saturation. By introducing a well-defined smooth function, a robust adaptive control algorithms are developed to deal with the problem of asymmetric non-smooth saturation. Unlike most of the existing control schemes for the uncertain nonlinear system, which requires...
The System identification explores ways to obtain mathematical models of an unknown system. However, as a result from the intrinsic random nature of system or from the environment noise, it is very hard to find a perfect mathematical representation of a real system. This paper aims to evaluate the Maximum Correntropy Criterion (MCC) performance using the gradient descent and the Fixed-Point. Both...
This paper treats a robust neural control strategy for discrete time uncertain nonlinear systems affected by parameters uncertainties. The control approach is based on an inverse neural model (INM) trained using a specialized learning technique. The importance of the presented approach is the use of a sliding mode backpropagation algorithm (SM-BP) for the learning of the direct neural model (DNM)...
With the rapid expansion of data scale, big data mining and analysis have attracted increasing attention. Outlier detection as an important task of data mining is widely used in many applications. However, conventional outlier detection methods have difficulty handling large-scale datasets. In addition, most of them typically can only identify global outliers and are over sensitive to parameters variation...
Sub-pixel accuracy in registration of synthetic aperture radar (SAR) images is still a challenging task in remote sensing applications. Speeded Up Robust Feature (SURF) is one of the most popularly used method for feature detection and description of SAR images. But using SURF alone in registration cannot give accurate matching in corresponding features, as it contains many wrong correspondences called...
In the cooperative data exchange problem, a set of clients share a lossless broadcast channel. Each client initially has a subset of packets in the ground set X, and wishes to learn all packets in X. The clients exchange their packets with each other by broadcasting coded or uncoded packets. In this paper, we consider a generalization of this problem for the settings in which an unknown (but of a...
We show an essentially tight bound on the number of adaptively chosen statistical queries that a computationally efficient algorithm can answer accurately given n samples from an unknown distribution. A statistical query asks for the expectation of a predicate over the underlying distribution, and an answer to a statistical query is accurate if it is “close” to the correct expectation over the distribution...
Non-rigid point set registration is a fundamental problem for many computer vision technologies. In this paper, we proposed a new non-rigid point set registration method based on coherent spatial mapping (CSM) and local geometrical constraint. Our central idea is to express each point as a weighted sum of several nearest neighbors and the same relation holds after the transformation. The registration...
Model Predictive Control (MPC) based relative motion control is developed for rendezvous of a follower spacecraft with a leader spacecraft. Debris Avoidance Maneuver operates in rendezvous phase and Line of Sight Maneuvers during terminal phase. In this approach, the optimal control sequence is generated over finite horizon by considering the measurement of the state in every guidance step for different...
Trust and reputation are commonly considered critical concepts in open dynamic multi-agent systems, where agents must rely on their peers to achieve their goals. Several computational trust models have been proposed to manage trust in such situation. The diversity of those models makes user confused about which one to choose. Different testbeds were proposed to evaluate trust and reputation systems...
In this paper, we study discrete and continuous versions of the LASSO in order to solve the deconvolution problem. We shed light on the Non Degenerate Source Condition, a property which yields support robustness for both the continuous and discrete problems. More precisely, we show that this property yields exact support recovery in the continuous case and the estimation of twice the number of spikes...
This paper addresses the importance and challenges of establishing cooperation among self-interested agents in multiagent systems (MAS). We study MAS operating on highly-connected random and scale-free (SF) networks. However, we emphasize SF networks as these are prevalent in society and nature. Existing imitation-based approaches for cooperation have been shown to not fare very well in these highly-connected...
Crowdsourcing has shown great potential in obtaining large-scale and cheap labels for different tasks. However, obtaining reliable labels is challenging due to several reasons, such as noisy annotators, limited budget and so on. The state-of-the-art approaches, either suffer in some noisy scenarios, or rely on unlimited resources to acquire reliable labels. In this article, we adopt the learning with...
In this paper, an orientation and scale invariant binary descriptor is proposed, which can be used in key-points matching systems. Conventionally, a binary descriptor is generated by comparing the intensities of pixels directly, such as those in Binary Robust Independent Elementary Features (BRIEF) and Oriented FAST and Rotated BRIEF (ORB). However, comparing intensities of pixels may lose the texture...
This paper presents an adaptive fuzzy moving sliding mode control for a class of uncertain Multi-Input Multi-Output (MIMO) nonlinear underactuated systems. The proposed control law involves a Proportional Integral control (PI) to reduce the chattering phenomenon caused by the discontinuous term in the classical sliding mode technique. The uncertain system functions are predicted by fuzzy logic systems...
In this paper, the problem of H∞ group consensus is addressed for networks of agents modeled by single-integrator with model uncertainty and external disturbance. The first part of the work is to show that the group consensus with desired H∞ performance can be achieved under some sufficient conditions that are established in terms of the structure and strength of the couplings among agents. Then given...
Green traffic engineering (TE) solutions play a central role in minimizing the energy expenditure of a network where they seek the minimal links/routers/switches required to support a given traffic demand. A key limitation, however, is that they are not designed to be robust against random traffic demands. To this end, this paper reports the first robust, green TE solution, called Green-PolyH, that...
Negotiations among autonomous agents have gained a mass of attention from a variety of communities in the past decade. This paper deals with a prominent type of automated negotiations, namely, multilateral multi-issue negotiation that runs under real-time constraints and in which the negotiating agents have no prior knowledge about their opponents' preferences over the space of negotiation outcomes...
Shopping experience is important for both citizens and tourists. We present IntelligShop, a novel location-based augmented reality application that supports intelligent shopping experience in malls. As the key functionality, IntelligShop provides an augmented reality interface -- people can simply use ubiquitous smartphones to face mall retailers, then IntelligShop will automatically recognize the...
Machine learning and data mining have become ubiquitous tools in modern computing applications and large enterprise systems benefit from its adaptability and intelligent ability to infer patterns that can be used for prediction or decision-making. Great success has been achieved by applying machine learning and data mining to the security settings for large dataset, such as in intrusion detection,...
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