Photonic delay systems have revolutionized the hardware implementation of Recurrent
Neural Networks and Reservoir Computing in particular. The fundamental principles of …

Consistency is an extension to generalized synchronization which quantifies the degree of
functional dependency of a driven nonlinear system to its input. We apply this concept to …

Adapting to regularities of the environment is critical for biological organisms to anticipate
events and plan. A prominent example is the circadian rhythm corresponding to the …

We employ reservoir computing for a reconstruction task in coupled chaotic systems, across
a range of dynamical relationships including generalized synchronization. For a drive …

We study and analyze the fundamental aspects of noise propagation in recurrent as well as
deep, multilayer networks. The motivation of our study is neural networks in analog …

Nonlinear dynamical systems exhibiting inherent memory can process temporal information
by exploiting their responses to input drives. Reservoir computing is a prominent approach …

We numerically perform the classification of IQ-modulated radiofrequency signals using
reservoir computing based on narrowband optoelectronic oscillators (OEOs) driven by a …

The ability of discrete-time nonlinear recurrent neural networks to store time-varying small
input signals is investigated with mean-field theory. The combination of a small input …

We describe a technique which minimizes the amount of neurons in the hidden layer of a
random recurrent neural network (rRNN) for time series prediction. Merging Takens-based …

This paper presents an interpretable neural system—termed Evolving Long-term Cognitive
Network—for pattern classification. The proposed model was inspired by Fuzzy Cognitive …