Sideslip angle, yaw rate, and vehicle speed are critical for intelligent chassis control. Existing vehicle state estimation studies seldom simultaneously consider the effects of data loss and noise variations on estim...
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Influence maximization plays a pivotal role in areas such as cybersecurity, public opinion management, and viral marketing. However, conventional methods for influence maximization grapple with challenges such as seed...
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The continuum manipulator has the characteristics of flexibility and compliance. However, the path re-planning problem of the continuum manipulator remain challenging. Aiming at the issue of path replanning for contin...
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Applying the noisy channel model to search query spelling correction requires an error model and a language model. Typically, the error model relies on a weighted string edit distance measure. The weights can be learn...
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In this paper, an adaptive grid DOA estimation algorithm based on sparse Bayesian learning (LMSBL) is proposed. Compared with the traditional off-grid EM-SBL algorithm, the proposed algorithm overcomes the problem of ...
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The failure mechanism as well as the life prediction of neutron tubes have attracted much attention for the wide application of neutron tubes in many domains. In this paper, the failure modes of prefabricated deuteriu...
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The law of total variance states that the unconditional variance of a random variable Y is the sum of (a) the variance of the conditional expectation of Y given X and (b) the expectation of the conditional variance ...
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Maximizing monotone submodular functions under cardinality constraints is a classic optimization task with several applications in data mining and machine learning. In this paper we study this problem in a dynamic env...
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Maximizing monotone submodular functions under cardinality constraints is a classic optimization task with several applications in data mining and machine learning. In this paper we study this problem in a dynamic environment with consistency constraints: elements arrive in a streaming fashion and the goal is maintaining a constant approximation to the optimal solution while having a stable solution (i.e., the number of changes between two consecutive solutions is bounded). We provide algorithms in this setting with different trade-offs between consistency and approximation quality. We also complement our theoretical results with an experimental analysis showing the effectiveness of our algorithms in real-world instances. Copyright 2024 by the author(s)
For sparse Direction-of-Arrival (DOA) estimation problems, sparse Bayesian learning (SBL) has achieved excellent performance. As a combination of observation and priors, SBL-based methods exploit priors as regularizat...
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In this paper, we propose a blind detection method based on asymmetric constellations for multiple-input multiple-output (MIMO) systems. In block fading channels, the transmission information sequence is randomly and ...
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