STG-DMD (Sparse-Coded Time-Delay Graph Dynamic Mode Decomposition) is a data-driven framework for modeling nonlinear dynamics on graph structures. It integrates: StgDmd/ ├── code/ │ ├── artificial/ │ ...
Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...
1 School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, China 2 School of Information Engineering, East University of Heilongjiang, Harbin, China Recognizing ...
Abstract: The distributed nonlinear adaptive graph filter (DNAGF) is developed with the single nonlinear graph filter model (NGFM) to handle streaming datasets. However, the current DNAGFs tend to ...
In this work, we provide some sufficient conditions to study the global asymptotic stability of the endemic equilibrium for certain models in mathematical epidemiology with nonlinear incidence and ...
This paper introduces a novel hierarchical graph-based long short-term memory network designed for predicting the nonlinear seismic responses of building structures. We represent buildings as graphs ...
Abstract: Graph wavelet transforms allow for the effective representation of signals that are defined over irregular domains. The transform coefficients should be sparse, and encode salient features ...
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