Showing 141 - 160 results of 5,816 for search '"LaTeX"', query time: 0.27s Refine Results
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    <inline-formula> <tex-math notation="LaTeX">$L_p$ </tex-math></inline-formula>-Norm-Based Sparse Regularization Model for License Plate Deblurring by Chenping Zhao, Yingjun Wang, Hongwei Jiao, Jingben Yin, Xuezhi Li

    Published 2020-01-01
    “…We propose an <inline-formula> <tex-math notation="LaTeX">$L_{p}$ </tex-math></inline-formula>-norm-based sparse regularization model for license plate deblurring, which is motivated by distinctive properties of license plate images. …”
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    <inline-formula> <tex-math notation="LaTeX">$HT$ </tex-math></inline-formula>: A Novel Labeling Scheme for k-Hop Reachability Queries on DAGs by Ming Du, Anping Yang, Junfeng Zhou, Xian Tang, Ziyang Chen, Yanfei Zuo

    Published 2019-01-01
    “…Given a directed acyclic graph (<italic>DAG</italic>), a <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-hop reachability query <inline-formula> <tex-math notation="LaTeX">${u}\xrightarrow {?…”
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    Certain Bounds Related to Multi-Parameterized <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-Fractional Integral Inequalities and Their Applications by Chunyan Luo, Bo Yu, Yao Zhang, Tingsong Du

    Published 2019-01-01
    “…A <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-fractional integral identity with multiple parameters is investigated. …”
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    Higher-Order State and Disturbance Observer With <inline-formula> <tex-math notation="LaTeX">$O(T^{3})$ </tex-math></inline-formula> Errors for Linear Systems by Yue Fu, Dongwei Wang

    Published 2019-01-01
    “…When the usual assumptions on the disturbance are satisfied, the magnitudes of the state and disturbance estimate errors of the system are proved to be on the order of <inline-formula> <tex-math notation="LaTeX">$O(T^{3})$ </tex-math></inline-formula>, which is much less than <inline-formula> <tex-math notation="LaTeX">$O(T^{2})$ </tex-math></inline-formula> produced by the proportional-integral-observer (PIO). …”
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