Reservoir Computing

Coupled Nonlinear Delay Systems As Deep Convolutional Neural Networks

Neural networks are currently transforming the field of computer algorithms, yet their emulation on current computing substrates is highly inefficient. Reservoir computing was successfully implemented on a large variety of substrates and gave new …

Coupled Delay Systems For Brain-Inspired Computing

Neural networks are transforming the field of computer algorithms, yet their emulation on current computing substrates is highly inefficient. Reservoir computing was successfully implemented on a large variety of substrates and gave new insight in …

Efficient Design of Hardware-Enabled Reservoir Computing in FPGAs

In this work, we propose a new approach towards the efficient optimization and implementation of reservoir computing hardware reducing the required domain expert knowledge and optimization effort. First, we adapt the reservoir input mask to the …

Bio-inspired computing

Conceiving next-generation computing principles inspired by biological systems such as the human brain.

On Theory and Modeling of Complex Nonlinear Delay Dynamics

The motivation behind our research in dynamical systems is an implementation of brain-inspired hardware. In the first part of the talk, we discuss the emergence of complex patterns in a nonlinear delay oscillator. Those self-organized formations …