Zobrazeno 1 - 10
of 107 689
pro vyhledávání: '"Time-variant"'
When facing time-variant problems in analog computing, the desirable RNN design requires finite-time convergence and robustness with respect to various types of uncertainties, due to the time-variant nature and difficulties in implementation. It is v
Externí odkaz:
http://arxiv.org/abs/2411.07570
Autor:
He, Jiakuang, Wu, Dongqing
Time-variant standard Sylvester-conjugate matrix equations are presented as early time-variant versions of the complex conjugate matrix equations. Current solving methods include Con-CZND1 and Con-CZND2 models, both of which use ode45 for continuous
Externí odkaz:
http://arxiv.org/abs/2411.02333
Autor:
He, Jiakuang, Wu, Dongqing
Large-scale linear equations and high dimension have been hot topics in deep learning, machine learning, control,and scientific computing. Because of special conjugate operation characteristics, time-variant complex conjugate matrix equations need to
Externí odkaz:
http://arxiv.org/abs/2408.14057
Autor:
Simionato, Riccardo, Fasciani, Stefano
This paper presents a method for modeling optical dynamic range compressors using deep neural networks with Selective State Space models. The proposed approach surpasses previous methods based on recurrent layers by employing a Selective State Space
Externí odkaz:
http://arxiv.org/abs/2408.12549
Autor:
He, Jiakuang, Wu, Dongqing
Complex conjugate matrix equations (CCME) have aroused the interest of many researchers because of computations and antilinear systems. Existing research is dominated by its time-invariant solving methods, but lacks proposed theories for solving its
Externí odkaz:
http://arxiv.org/abs/2406.12783
Australian Rules Football is a field invasion game where two teams attempt to score the highest points to win. Complex machine learning algorithms have been developed to predict match outcomes post-game, but their lack of interpretability hampers an
Externí odkaz:
http://arxiv.org/abs/2405.12588
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Recent advancements in neural rendering techniques have significantly enhanced the fidelity of 3D reconstruction. Notably, the emergence of 3D Gaussian Splatting (3DGS) has marked a significant milestone by adopting a discrete scene representation, f
Externí odkaz:
http://arxiv.org/abs/2405.13694