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Controlling non-affine non-linear systems is a challenging problem in control theory. In this paper, we consider adaptive neural control of a completely non-affine pure-feedback system using radial basis function (RBF) neural networks (NN). An ISS-modular approach is presented by combining adaptive neural design with the backstepping method, input-to-state(More)
In this paper, adaptive neural control schemes are proposed for two classes of uncertain multi-input/multi-output (MIMO) nonlinear systems in block-triangular forms. The MIMO systems consist of interconnected subsystems, with couplings in the forms of unknown nonlinearities and/or parametric uncertainties in the input matrices, as well as in the system(More)
This paper is concerned with the control of nonlinear pure-feedback systems with unknown nonlinear functions. This problem is considered di/cult to be dealt with in the control literature, mainly because that the triangular structure of pure-feedback systems has no a/ne appearance of the variables to be used as virtual controls. To overcome this di/culty,(More)
A novel image encryption scheme is proposed based on a nonlinear chaotic map (NCM). There are two rounds in this scheme which are only based on the XOR operation. In each round, the pixel gray values are modified from the first pixel to the last pixel firstly, and then the modified image is encrypted from the last pixel to the first pixel in the inverse(More)
In this paper, direct adaptive neural-network (NN) control is presented for a class of affine nonlinear systems in the strict-feedback form with unknown nonlinearities. By utilizing a special property of the affine term, the developed scheme,avoids the controller singularity problem completely. All the signals in the closed loop are guaranteed to be(More)
One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference(More)
Wireless sensor networks routing protocols always neglect security problem at the designing step, while plenty of solutions of this problem exist, one of which is using key management. Researchers have proposed many key management schemes, but most of them were designed for flat wireless sensor networks, which is not fit for cluster-based wireless sensor(More)
Recent studies have shown strong temporal correlations between past climate changes and societal crises. However, the specific causal mechanisms underlying this relation have not been addressed. We explored quantitative responses of 14 fine-grained agro-ecological, socioeconomic, and demographic variables to climate fluctuations from A.D. 1500-1800 in(More)
In the same way Internet standards have connected heterogeneous computing systems, we predict robot communication standards will speed research and development of teleoperated robots. In this paper, a preliminary specification is presented for interoperability among robotic telesurgery systems. This is a first step towards developing a full telerobotics(More)
Transient receptor potential vanilloid (TRPV) channels are nonselective cation channels pertinent to diverse physiological functions. Multiple TRPV channel subtypes have been identified in different tissues and cloned. The aim of this study was to investigate the role of TRPV channels in hypoxia-induced proliferation of human pulmonary artery smooth muscle(More)