In this paper, we consider the global output feedback stabilization problem for a class of nonlinear planar systems under a more general growth condition. The nonlinearities in such a system are bounded by both lower-...
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This paper addresses the evaluation of the capacity credit of RES plants in the Greek power system. Five different RES technologies are considered, namely wind, PV, small hydro, biomass, and cogeneration. The methodol...
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ISBN:
(纸本)9781467356688
This paper addresses the evaluation of the capacity credit of RES plants in the Greek power system. Five different RES technologies are considered, namely wind, PV, small hydro, biomass, and cogeneration. The methodology adopted uses widely accepted power system reliability indices, such as the loss of load probability (LOLP) and the loss of load expectation (LOLE), computed using the capacity outage probability table (COPT). A three-step procedure for the calculation of the capacity credit for all RES technologies using the effective load carrying capability (ELCC) metric is implemented. Using real historic operational data of the Greek power system, the capacity credit of all RES technologies for the year 2011 are derived. Sensitivity results regarding the effect of the initial installed capacity and the new entrant capacity on the capacity credit are also presented.
We present a novel real-time implementation of local phase feature extraction from volumetric image data based on 3D directional (log-Gabor) filters. We achieve drastic performance gains without compromising the signa...
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ISBN:
(纸本)9781467364560
We present a novel real-time implementation of local phase feature extraction from volumetric image data based on 3D directional (log-Gabor) filters. We achieve drastic performance gains without compromising the signal-to-noise ratio by pre-computing the filters and adaptive noise estimation parameters, and streamlining the remainder of the computations to efficiently run on a multi-processor graphic processing unit (GPU). We validate our method on clinical ultrasound data and demonstrate a 15-fold speedup in computation time over state-of-the art methods, which could potentially facilitate a wide range of practical applications for real-time image-guided procedures.
A useful measure is presented for comparison of distinct cryptosystems, including (i) the RSA algorithm, (ii) ElGamal algorithm, (iii) a cryptosystem based on radio background noise (RBN), and (iv) a new cryptosystem ...
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ISBN:
(纸本)9781479900312
A useful measure is presented for comparison of distinct cryptosystems, including (i) the RSA algorithm, (ii) ElGamal algorithm, (iii) a cryptosystem based on radio background noise (RBN), and (iv) a new cryptosystem based on chaos phenomena. The four cryptosystems are implemented to have the same computational power, and are compared through the marginal probability mass functions (mpmf). This paper shows experimentally that the chaos-based modular dynamical cryptosystem is (i) strong to statistical cryptanalysis by leaving no patterns or hooks in the ciphertexts and (ii) faster than the selected algorithms from public-key cryptography (RSA) and elliptic curve cryptography (ElGamal).
This paper presents useful measures for comparison of distinct cryptosystems, including (i) the public-key cryptography RSA algorithm, (ii) the elliptic-curve cryptography ElGamal algorithm, (iii) a cryptosystem based...
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This paper presents useful measures for comparison of distinct cryptosystems, including (i) the public-key cryptography RSA algorithm, (ii) the elliptic-curve cryptography ElGamal algorithm, (iii) a cryptosystem based on radio background noise (RBN), and (iv) a new cryptosystem based on chaos phenomena in cellular automata. The comparison is based on (i) a single-scale measure (i.e., the marginal probability mass functions (mpmf), and (ii) a poly-scale measure (i.e., the finite-sense stationarity, FSS10). Both comparison approaches use the same plaintext and computational power when testing the four cryptosystems. This paper shows experimentally that the chaos based modular dynamical cryptosystem is (i) strong to single-scale statistical cryptanalysis by leaving no patterns in the ciphertexts, (ii) strong to poly-scale cryptanalysis by having a smaller stationarity window than the alternative cryptosystems, and (iii) faster than the selected algorithms from RSA, ElGamal, and natural sources of randomness (RBN).
Cognitive systems call for wireless communications with antennas having stringent requirements. For example, software-defined radio, cognitive radio, and cognitive sensor networks operate over very wide bandwidth, wit...
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Cognitive systems call for wireless communications with antennas having stringent requirements. For example, software-defined radio, cognitive radio, and cognitive sensor networks operate over very wide bandwidth, with small dimensions, high gain, and omnidirectionally. A candidate capable of addressing such requirements is the fractal antenna. This paper describes selected simulations results of the following two fractal antenna: Koch and Minkowski. The variation trends of the voltage standing-wave ratio, the reflection coefficient, and the S11 parameters of the antenna have been studied for several successive iterates of the fractal shapes.
This paper describes the application of extended and unscented Kalman filters for the identification of uncertainties in a process. The extended Kalman filter (EKF) is an optimal linear recursive algorithm that offers...
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This paper describes the application of extended and unscented Kalman filters for the identification of uncertainties in a process. The extended Kalman filter (EKF) is an optimal linear recursive algorithm that offers a solution to the filtering problem. The EKF is based on a first-order Taylor expansion to approximate the measurement and process models. This approach may cause the estimation process to diverge. Consequently, alternatives (e.g., the unscented Kalman filter, UKF) based on a fixed number of points to represent a Gaussian distribution have been introduced. The EKF and UKF have been applied for the identification of uncertainty in the attitude determination process for small satellites based on noisy measurements collected from Sun sensors and three-axis magnetometers. Simulation results indicate that the EKF and UKF perform equally well when small initial errors are present. However, when large errors are introduced, the UKF leads to a faster convergence and achieves a higher more accurate estimate of the state of the system.
Adding value to action-selection through reinforcement-learning provides a mechanism for modifying future decisions. This behavioral-level modulation is vital for performing in complex and dynamic environments. In thi...
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ISBN:
(纸本)9781629933122
Adding value to action-selection through reinforcement-learning provides a mechanism for modifying future decisions. This behavioral-level modulation is vital for performing in complex and dynamic environments. In this paper we focus on a class of biologically inspired feed-forward spiking neural networks capable of action-selection via reinforcement-learning. The networks are embodied in a minimal virtual agent and their ability to learn two simple games through reinforcement and punishment is explored. There is no bias or understanding of the task inherent to the network and all of the dynamics emerge based on environmental interactions. Value of an action takes the form of reinforcement and punishment signals. One novel aspect of these networks is that they obey the constraints of neuromorphic hardware currently being developed, including the DARPA SyNAPSE neuromorphic chips for very low power spiking model implementations. The simulation results demonstrate the performance of these models for a variant of classic pong as well as a first-person shooter. Embodying models like these in games creates virtual environments with varying levels of detail that are ideal for testing spiking neural networks. In addition, the results suggest that these models could serve as building blocks for the control of more complex robotic systems that are embodied in both virtual and real environments.
The electric power infrastructure is transforming into a smarter, increasingly flexible, and more efficient system with the potential to play an integral role in the changing energy landscape. This paper and the accom...
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ISBN:
(纸本)9781479901777
The electric power infrastructure is transforming into a smarter, increasingly flexible, and more efficient system with the potential to play an integral role in the changing energy landscape. This paper and the accompanying tutorial session at the 2013 American Control Conference provide an overview of this transformation. It then highlights three emerging optimization and controls techniques that can help facilitate the necessary changes to power grid design, operation and management.
The primary goal of the workshop is to showcase cutting edge research on the intersection of Recommender systems and Semantic Technologies, by taking the best of the two worlds. This combination may provide the RecSys...
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