A new method of topological analysis for networks containing nonreciprocal components and mutual inductance is presented. The components are required to have two, three, or four terminals and an admittance matrix. The...
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A new method of topological analysis for networks containing nonreciprocal components and mutual inductance is presented. The components are required to have two, three, or four terminals and an admittance matrix. The difference between the present method and other known methods is the result of allowing tree and two-tree admittance parameters to be a function of the shape and element content of corresponding trees and two-trees. No modification of the original network is required and for node determinant and diagonal cofactor calculations, no sign is appended to tree and two-tree parameters. The method is illustrated with a transistor amplifier.
The reversal of a program execution can be helpful for several purposes. The reverse mode of automatic differentiation, parameter estimation, and debugging represent some of the tasks that may require the intermediate...
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The reversal of a program execution can be helpful for several purposes. The reverse mode of automatic differentiation, parameter estimation, and debugging represent some of the tasks that may require the intermediate values of a calculation in reverse order. The recording of a complete execution log forms the simplest approach to providing the data required for the reversal. However, this "store-everything" method causes an enormous demand for memory. The generation of the execution log piece by piece offers the possibility to reduce the storage requirement. To that end the forward calculation is restarted from suitably placed checkpoints leading to a more or less complicated reversal schedule. This paper deals with the reversal of evaluation procedures that consist of a sequence of time steps with varying computational complexity. We present a new search algorithm for determining a reversal schedule that minimizes the runtime of the reversal process for a given number of checkpoints. By exploiting a certain monotonicity property, the search algorithm based on dynamic programming can be made to grow only quadratically with the number of time steps to be reverted. We report the runtime savings that can be achieved performing the reversal with an optimal, i.e. time-minimal, reversal schedule for a test problem based on Burgers' equation.
This article considers the problem of target detection for applications with limited training samples. Dimensionality reduction in the angle-Doppler domain is considered. An algorithm for selecting the best angle-Dopp...
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This article considers the problem of target detection for applications with limited training samples. Dimensionality reduction in the angle-Doppler domain is considered. An algorithm for selecting the best angle-Doppler channels that maximize the output signal-to-clutter-plus-noise ratio in space-time adaptive processing (STAP) is proposed. Compared with several existing STAP methods, the proposed method can achieve better clutter suppression performance at lower computational complexities when the degrees of freedom of the STAP system are fixed. Moreover, the proposed method can help address the issue of training data shortage, which may be particularly attractive for heterogeneous scenarios. Simulations are conducted for validating the proposed method and demonstrating their high performance.
For certain computational models, a constant-factor time hierarchy theorem is known, showing that a constant-factor difference in time bounds makes a difference in problem-solving power (unlike the situation with Turi...
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For certain computational models, a constant-factor time hierarchy theorem is known, showing that a constant-factor difference in time bounds makes a difference in problem-solving power (unlike the situation with Turing machines). In this paper we apply the classic "translational technique" (padding) to these hierarchies and show that they are tighter than indicated by the previous proofs. (C) 2003 Published by Elsevier Science B.V.
Orthogonal frequency code division multiple access (OFCDMA) system is one of the most promising multi-user wireless communications systems. It outperforms orthogonal frequency division multiplexing (OFDM) and multi-ca...
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Orthogonal frequency code division multiple access (OFCDMA) system is one of the most promising multi-user wireless communications systems. It outperforms orthogonal frequency division multiplexing (OFDM) and multi-carrier CDMA (MC-CDMA) through utilisation of two-dimensional spreading. This study proposes a downlink air interface that targets data rate increase and bit error rate (BER) performance enhancement with low complexity receiver. The proposed system is an integration of space-time spreading (STS) and OFCDMA that exploits transmit diversity needed for BER enhancing and data rate boosting with low complexity advantage. Further BER improvement was achieved using an effective iterative interference cancellation (IIC) algorithm at the receiver. Analytical and complexity analyses for the proposed system performance are presented in addition to simulation results. The proposed system attains better performance with lower complexity compared to the STS-aided direct sequence MC-CDMA that uses beamforming as a closed-loop transmit diversity. Moreover, the effect of frequency domain spreading factor with different number of iteration loops is investigated. The achieved BER performance was very close to maximal ratio receive combining system with 1Tx and 4Rx. A considerable improvement was obtained by increasing the number of IIC iteration loops. The system performance was enhanced significantly with the frequency domain spreading factor increase.
Reverse-time migration can accurately image complex geologic structures in anisotropic media. Extended images at selected locations in the Earth, i.e., at common-image-point gathers, carry rich information to characte...
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Reverse-time migration can accurately image complex geologic structures in anisotropic media. Extended images at selected locations in the Earth, i.e., at common-image-point gathers, carry rich information to characterize the angle-dependent illumination and to provide measurements for migration velocity analysis. However, characterizing the anisotropy influence on such extended images is a challenge. Extended common-image-point gathers are cheap to evaluate since they sample the image at sparse locations indicated by the presence of strong reflectors. Such gathers are also sensitive to velocity error that manifests itself through moveout as a function of space and time lags. Furthermore, inaccurate anisotropy leaves a distinctive signature in common-image-point gathers, which can be used to evaluate anisotropy through techniques similar to the ones used in conventional wavefield tomography. It specifically admits a V-shaped residual moveout with the slope of the "V" flanks depending on the anisotropic parameter. regardless of the complexity of the velocity model. It reflects the fourth-order nature of the anisotropy influence on moveout as it manifests itself in this distinct signature in extended images after handling the velocity properly in the imaging process. Synthetic and real data observations support this assertion.
We present an approach where probabilistic logic is combined with default reasoning from conditional knowledge bases in Kraus et al.'s System P, Pearl's System Z, and Lehmann's lexicographic entailment. Th...
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We present an approach where probabilistic logic is combined with default reasoning from conditional knowledge bases in Kraus et al.'s System P, Pearl's System Z, and Lehmann's lexicographic entailment. The resulting probabilistic generalizations of default reasoning from conditional knowledge bases allow for handling in a uniform framework strict logical knowledge, default logical knowledge, as well as purely probabilistic knowledge. Interestingly, probabilistic entailment in System P coincides with probabilistic entailment under g-coherence from imprecise probability assessments. We then analyze the semantic and nonmonotonic properties of the new formalisms. It turns out that they all are proper generalizations of their classical counterparts and have similar properties as them. In particular, they all satisfy the rationality postulates of System P and some Conditioning property. Moreover, probabilistic entailment in System Z and probabilistic lexicographic entailment both satisfy the property of Rational Monotonicity and some Irrelevance property, while probabilistic entailment in System P does not. We also analyze the relationships between the new formalisms. Here, probabilistic entailment in System P is weaker than probabilistic entailment in System Z, which in turn is weaker than probabilistic lexicographic entailment. Moreover, they all are weaker than entailment in probabilistic logic where default sentences are interpreted as strict sentences. Under natural conditions, probabilistic entailment in System Z and lexicographic entailment even coincide with such entailment in probabilistic logic, while probabilistic entailment in System P does not. Finally, we also present algorithms for reasoning under probabilistic entailment in System Z and probabilistic lexicographic entailment, and we give a precise picture of its complexity. (c) 2005 Elsevier B.V. All rights reserved.
Active pulsating power buffering (APPB) is an emerging technology that can effectively minimize the energy storage requirement of single-phase power conversion systems, potentially leading to high density and high rel...
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Active pulsating power buffering (APPB) is an emerging technology that can effectively minimize the energy storage requirement of single-phase power conversion systems, potentially leading to high density and high reliability design. Nonetheless, the implementation of APPB generally requires the addition of excessive number of sensors in the circuit. Employing many sensors not only increases the system's volume and cost, but also undermines the system's robustness. Existing methods of reducing the sensor count in single-phase converters with an APPB suffer from issues such as high design complexity, noise sensitivity, and/or computational complexity. In this article, a simplified algebraic estimation technique is proposed to tackle the high sensor count problem. The proposed technique is intuitive to design and applicable to different topologies. It can effectively reduce the number of sensors while yielding similar or even better system's performance than that with a full set of sensors. Moreover, the technique features very low computational complexity, and can thus be easily implemented by low-cost microcontrollers. Experiments are conducted to verify the feasibilities of the proposed estimation and sensor reduction method. With this method, the sensor count can be reduced by 50%, while achieving a nearly 20-times computational time reduction as compared to that of the conventional method.
This paper addresses a structural design problem in control systems, and explicitly takes into consideration the possible application to large-scale systems. More precisely, we aim to determine and characterize the mi...
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This paper addresses a structural design problem in control systems, and explicitly takes into consideration the possible application to large-scale systems. More precisely, we aim to determine and characterize the minimum number of manipulated state variables ensuring structural controllability of switched linear continuous-time systems. Towards this goal, we provide a new necessary and sufficient condition that leverages both graph-theoretic and algebraic properties required to ensure feasibility of the solutions. With this new condition, we show that a solution can be determined by an efficient procedure, i.e., polynomial in the number of state variables. In addition, we also discuss the switching signal properties that ensure structural controllability and the computational complexity of determining these sequences. In particular, we show that determining the minimum number of modes that a switching signal requires to ensure structural controllability is NP-hard. (C) 2016 Elsevier Ltd. All rights reserved.
Qualitative trend analysis (QTA) is a data-driven semi-quantitative technique that has been used for process monitoring and fault detection and diagnosis (FDD). Though QTA provides quick and accurate diagnosis-the inc...
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Qualitative trend analysis (QTA) is a data-driven semi-quantitative technique that has been used for process monitoring and fault detection and diagnosis (FDD). Though QTA provides quick and accurate diagnosis-the increase in computational comlexity of QTA with the increase in the number of sensors used for diagnosis-may prohibit its real-time application for very large-scale plants. In most of the chemical plants, the measurements are highly redundant and this redundancy can be exploited by performing principal component analysis (PCA) on the measured data. In this paper, we present a PCA-QTA technique for fault diagnosis (FD) in large-scale plants. Essentially, QTA is applied on the principal components rather than on the sensor data. The proposed approach is tested on the Tennessee Eastman (TE) process. The reduction in computational complexity in trend-extraction is about 40%. This reduction in computational complexity is expected to increase considerably for larger processes.
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