Robust prediction of chaotic systems with random errors using dynamical system deep learning
To predict nonlinear dynamical systems, a novel method called the dynamical system deep learning (DSDL), which is based on the state space reconstruction (SSR) theory and utilizes time series data for model training, was recently proposed.
Zixiang Wu +5 more
doaj +1 more source
Wong-Zakai type approximations of rough random dynamical systems by smooth noise [PDF]
Qiyong Cao, Hui Gao, Björn Schmalfuß
openalex +1 more source
A Spectral Approach for Quenched Limit Theorems for Random Expanding Dynamical Systems [PDF]
D. Dragičević +3 more
openalex +1 more source
Existence and stability of time-fractional Keller-Segel-Navier-Stokes system with Poisson jumps. [PDF]
Divyabala K, Durga N.
europepmc +1 more source
Bridging developmental and statistical approaches to variation and evolution. [PDF]
Milocco L, Uller T.
europepmc +1 more source
A Comparative Study of RQA-Guided Attention Mechanisms with LSTM Autoencoder for Bearing Anomaly Detection. [PDF]
Hatipoğlu A, Yılmaz E.
europepmc +1 more source
Robust coexistence in competitive ecological communities. [PDF]
Lechón-Alonso P +4 more
europepmc +1 more source
Numerical modeling of dynamical systems with random delays
И Е Полосков
openalex +1 more source
A theory for self-sustained balanced states in absence of strong external currents. [PDF]
Angulo-Garcia D, Torcini A.
europepmc +1 more source

