In a cognitive radio (CR) scenario, we study the joint problem of spectrum sensing and jamming detection. Modelling the scenario as a multiple hypothesis testing problem, we analyse the probability of detection of the...
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In a cognitive radio (CR) scenario, we study the joint problem of spectrum sensing and jamming detection. Modelling the scenario as a multiple hypothesis testing problem, we analyse the probability of detection of the optimal detector in the sense of Neyman-Pearson theorem. We derive one exact form in terms of a series and a closed-form version. Moreover, we evaluate the asymptotic probability of detection, as it results in a simpler form to handle. In all of the above analysis, we consider the spatially correlated observation data. We further consider two practical scenarios where first we have no knowledge of the jammer's signal, and second where we have no knowledge of the noise power. We apply generalized likelihood ratio test in both of the cases. Simulation results confirm the accuracy of our asymptotic performance derivations.
An Active Disturbance Rejection based solution is proposed for the position control of a standard inverted pendulum system, demonstrating a largely model independent design that is distinctly different from existing m...
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ISBN:
(纸本)9781479947249
An Active Disturbance Rejection based solution is proposed for the position control of a standard inverted pendulum system, demonstrating a largely model independent design that is distinctly different from existing model-based designs from classical as well as modern control theory. The quality of the control loop is further improved with a unique double disturbance observer design, which rejects independently the disturbance and uncertainty in both the pendulum itself and the cart that carries it. This proposed approach offers a promising and practical solution because it's intuitive to understand and easy to tune, in addition to its strong performance and effectiveness shown in both simulation study and real time experimentation.
This paper proposes an adaptive frequency hopping (AFH) approach that allows Industrial Wireless Sensor Networks (IWSNs) to cognitively switch working channels for high transmission reliability. Assuming the communica...
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This paper proposes an adaptive frequency hopping (AFH) approach that allows Industrial Wireless Sensor Networks (IWSNs) to cognitively switch working channels for high transmission reliability. Assuming the communication spectrum state follows a Markov Process (MP), we build a theoretical AFH framework based on the theory of Markov Decision Process (MDP). With this decision-theoretic framework, we can achieve an AFH strategy that maximizes the expected cumulative transmission reliability over a finite horizon. Judging the high computational complexity of the proposed MDP model, we further propose a myopic AFH with reduced complexity by assuming that each channel evolves independently. Without additional computation burdens or control messages exchange between sensors, the proposed AFH strategies are centrally computed by the network manager. Simulations finally demonstrate the efficiency of the proposed AFH strategies.
In this paper, the tracking control problem of a 3-input 3-output nonlinear system is investigated and solved. By adopting and generalizing Zhang-gradient (ZG) method, as the novel combination of Zhang dynamics (ZD) a...
In this paper, the tracking control problem of a 3-input 3-output nonlinear system is investigated and solved. By adopting and generalizing Zhang-gradient (ZG) method, as the novel combination of Zhang dynamics (ZD) and gradient dynamics (GD), in a quite different way (i.e., with GD used additionally once more), a ZG controller group is designed and proposed for the tracking control of the aforementioned system. Furthermore, simulation results substantiate the efficacy of the proposed controller group in fulfilling the tracking control task of the 3-input 3-output (3I3O) system.
This paper presents the relatively complete theory for the two new numerical algorithms, i.e., E47 algorithm and 94LVI algorithm, for solving the quadratic program (QP) subject to inequality and bound constraints effi...
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ISBN:
(纸本)9781467371902
This paper presents the relatively complete theory for the two new numerical algorithms, i.e., E47 algorithm and 94LVI algorithm, for solving the quadratic program (QP) subject to inequality and bound constraints efficiently. Specifically, via the important “Bridge” theorems and with their proofs provided, the QP problem is converted equivalently into a piecewise-linear projection equation (PLPE). The E47 and 94LVI algorithms are thus developed to solve the PLPE and also the QP. Note that, compared with the previous achievements with only the sufficiency proved, strict proofs (i.e., both the sufficiency proofs and the necessity proofs) of the “Bridge” theorems are firstly presented. Besides, the convergence property of the two algorithms is analyzed in the paper, and theoretical proofs ensure the global linear convergence of the two algorithms about the final decision variable vector x, instead of the primal-dual decision variable vector y.
In recent years, extensive efforts have been committed to the temperature forecast work, and more and more studies have indicated that the temperature is rising. For the purpose of forecasting long-term temperature tr...
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In recent years, extensive efforts have been committed to the temperature forecast work, and more and more studies have indicated that the temperature is rising. For the purpose of forecasting long-term temperature trend, a temperature forecast method named multiple sine functions decomposition (MSFD) method is presented in this paper. Based on the numerical experiments for 12 Asia-Pacific (APAC) cities, the efficacy of the MSFD method and the warming trend of APAC region are substantiated. The core concept of the MSFD method is that, by decomposing a historical temperature sequence into sine waveforms, multiple sine functions are thus obtained and applied to forecasting the future temperature trend. Different degrees of warming in the ensuing 200 years are forecasted from the results of numerical experiments. In addition, we find that the high-latitude cities are generally more evident in terms of temperature change compared with those low-latitude cities. In summary, with the most possibility, the general temperature trend of APAC region is upward.
This paper considers solving the tracking and stabilizing control problems of the Chen chaotic system with multiplicative inputs. By using the Zhang-gradient (ZG) method, which combines Zhang dynamics (ZD) and gradien...
This paper considers solving the tracking and stabilizing control problems of the Chen chaotic system with multiplicative inputs. By using the Zhang-gradient (ZG) method, which combines Zhang dynamics (ZD) and gradient dynamic (GD), a ZG controller is obtained for solving the problems above. Moreover, another new ZG controller is designed by using the ZG method again. Simulation results further show the effectiveness and high efficiency of the ZG controllers.
In past decades, the online solution of inverse kinematics (IK) has always been a mathematically troublesome problem for redundant robot manipulators. Besides, the traditional IK approaches, such as the pseudo-inverse...
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In past decades, the online solution of inverse kinematics (IK) has always been a mathematically troublesome problem for redundant robot manipulators. Besides, the traditional IK approaches, such as the pseudo-inverse method, have to calculate the computationally expensive inverse (specifically, pseudo-inverse) of Jacobian matrix. To drastically and effectively avoid the Jacobian inversion and to obtain the accurate solution of the time-varying IK problem for redundant robot manipulators, a special type of inverse-free solution, namely of Z1G1 type, is thus proposed and investigated at the joint-acceleration level in this paper. In addition, we conduct the path-tracking simulations performed on three-link, four-link and five-link planar robot manipulators to substantiate the effectiveness and accuracy of such an inverse-free solution. Moreover, the experiment based on a six-link redundant robot manipulator hardware system illustrates the physical realizability of the proposed novel solution for handling the time-varying IK problem of the redundant robot manipulator(s) in an inverse-free manner.
In this paper, a special method called Zhang neuronet (ZN) is proposed and investigated for online solution of complex-valued time-varying linear inequalities (CVTVLI). Instead of employing a norm-based energy functio...
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In this paper, a special method called Zhang neuronet (ZN) is proposed and investigated for online solution of complex-valued time-varying linear inequalities (CVTVLI). Instead of employing a norm-based energy function in traditional gradient neuronet (GN) and related methods, the given ZN model is designed using a vector-valued error function and takes advantage of the first-order time-derivative information of time-varying coefficients involved in CVTVLI. Through adjusting the value of design parameter γ appropriately, superior convergence performance is achieved for the proposed ZN model for dealing with such a time-varying problem. Then, theoretical and simulative results are given to illustrate and substantiate the convergence property of the proposed ZN model. Besides, a GN model is developed and exploited to for the same CVTVLI solving. The comparison on transient behaviors of these two models further shows the efficacy and superiority of the proposed ZN model.
With growing economic and political influence in the world, the important role played by Oceania in population issues should not be neglected. So it is very important and urgent to find an effective way to make a prop...
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ISBN:
(纸本)9781467371902
With growing economic and political influence in the world, the important role played by Oceania in population issues should not be neglected. So it is very important and urgent to find an effective way to make a proper population projections. Nonetheless, the traditional methods focused on fertility and mortality may lead to the lack of all-sidedness in projection results. We realize that the historical data contain the internal mechanism of the population development, and the neuronet performs well with nonlinear data and the multifactor system. Therefore, in this report, we construct a 3-layer feed-forward neuronet equipped with a weights-and-structure-determination (WASD) algorithm to learn the historical data and project the population. With the neuronet well trained by over 1000-year historical data, we successfully project that the future Oceania population will keep a steady increasing trend in the coming fifteen years.
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