Showing 21 - 40 results of 8,891 for search '(competing OR computing) patterns', query time: 0.18s Refine Results
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    Discriminating neural ensemble patterns through dendritic computations in randomly connected feedforward networks by Bhanu Priya Somashekar, Upinder Singh Bhalla

    Published 2025-01-01
    “…Local convergence of such patterned activity as synaptic clusters on dendrites could help single neurons harness the potential of dendritic nonlinearities to decode neural activity patterns. …”
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    Pattern recognition method for the identification of Daiqu large yellow croaker based on computer vision by YU Xinjie, WU Xiongfei, SHEN Weiliang

    Published 2018-07-01
    “…A pattern recognition method based on computer vision was developed for the identification of Daiqu large yellow croaker. …”
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    Computation of monostatic RCS using adaptive sparsity pattern preconditioning with an MBF‐MLFMM approach by Carlos Delgado, Eliseo García, Felipe Cátedra

    Published 2024-12-01
    “…Abstract This work presents a numerical technique for the analysis of the Radar Cross Section (RCS) of large targets combining macro‐basis functions, the multilevel fast multipole method and the generation of near‐field preconditioners, using an approximate inverse matrix where the sparsity pattern is dynamic and computed considering an upper memory threshold. …”
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    Computational thinking in the context of higher education: Analytical review by E. K. Khenner

    Published 2024-02-01
    “…In computational thinking, cognitive skills include abstraction, decomposition, pattern recognition, algorithmisation, visualisation, logical thinking, communicative competence, the ability to present, structure and analyse data, and some others skills. …”
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    The Application of Entropy in Motor Imagery Paradigms of Brain–Computer Interfaces by Chengzhen Wu, Bo Yao, Xin Zhang, Ting Li, Jinhai Wang, Jiangbo Pu

    Published 2025-02-01
    “…<b>Background:</b> In motor imagery brain–computer interface (MI-BCI) research, electroencephalogram (EEG) signals are complex and nonlinear. …”
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