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Full Lyapunov Spectra of Random Neural Networks, Part I: Finite-Time and Asymptotic Theory
We develop a dynamical mean-field framework for the full finite-time and stationary asymptotic Lyapunov spectra of random recurrent neural networks. At finite observation time, an exact log-determinant representation of tangent-propagator singular values leads to a closed-contour matrix Dyson equati
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