# Performance boost of time-delay reservoir computing by non-resonant clock cycle

@article{Stelzer2020PerformanceBO, title={Performance boost of time-delay reservoir computing by non-resonant clock cycle}, author={Florian Stelzer and Andr{\'e} R{\"o}hm and Kathy L{\"u}dge and Serhiy Yanchuk}, journal={Neural networks : the official journal of the International Neural Network Society}, year={2020}, volume={124}, pages={ 158-169 } }

## 22 Citations

### Deep Time-Delay Reservoir Computing: Dynamics and Memory Capacity

- Computer ScienceChaos
- 2020

This work presents how the dynamical properties of a deep Ikeda-based reservoir are related to its memory capacity (MC) and how that can be used for optimization and presents two configurations that empower either high nonlinear MC or long time linear MC.

### The role of delay-times in delay-based Photonic Reservoir Computing

- Computer ScienceArXiv
- 2021

The existing literature on this subject is reviewed and the concept of delay-based reservoir computing is introduced in a manner that demonstrates that there is no predefined relationship between these two times-scales.

### Limitations of the recall capabilities in delay based reservoir computing systems

- Computer ScienceCognitive Computation
- 2020

The results suggest that even for constant readout dimension the total memory capacity is dependent on the ratio between the information input period, also called the clock cycle, and the time delay in the system.

### Insight into delay based reservoir computing via eigenvalue analysis

- Computer ScienceJournal of Physics: Photonics
- 2021

This paper applies the method exemplarily to a photonic laser system with feedback and compares the numerically computed recall capabilities with the eigenvalue spectrum, suggesting that any dynamical system used as a reservoir can be analysed in this way.

### Reservoir Computing with Delayed Input for Fast and Easy Optimisation

- Computer ScienceEntropy
- 2021

It is demonstrated that by including a time-delayed version of the input for various time series prediction tasks, good performance can be achieved with an unoptimised reservoir and it is shown that one unaltered reservoir can perform well on six different time series Prediction tasks at a very low computational expense.

### Master memory function for delay-based reservoir computers with single-variable dynamics

- Computer ScienceIEEE transactions on neural networks and learning systems
- 2022

This work shows that many delay-based reservoir computers considered in the literature can be characterized by a universal master memory function (MMF), and proposes an analytical description of the MMF that enables its efficient and fast computation.

### Impact of phase modulation on the performance of photonic delay-based reservoir computing with semiconductor lasers

- PhysicsPhotonics Europe
- 2022

In photonic reservoir computing, semiconductor lasers with delayed feedback have been used to efficiently solve difficult and time-consuming problems. The injection of data in these systems is often…

### Reservoir Computing with Diverse Timescales for Prediction of Multiscale Dynamics

- Computer SciencePhysical Review Research
- 2022

A reservoir computing model with diverse timescales by using a recurrent network of heterogeneous leaky integrator (LI) neurons is proposed, and it is demonstrated that a closed-loop version of the proposed model can achieve longer-term predictions compared to the counterpart with identical LI neurons depending on the hyperparameter setting.

### Deep neural networks using a single neuron: folded-in-time architecture using feedback-modulated delay loops

- Computer ScienceNature communications
- 2021

This work presents a method for folding a deep neural network of arbitrary size into a single neuron with multiple time-delayed feedback loops, which can fully represent standard Deep Neural Networks, encompasses sparse DNNs, and extends the DNN concept toward dynamical systems implementations.

### Improving Delay Based Reservoir Computing via Eigenvalue Analysis

- Computer ScienceArXiv
- 2020

It is shown that these two quantities are deeply connected, and thus the reservoir computing performance is predictable by analyzing the eigenvalue spectrum, and any dynamical system used as a reservoir can be analyzed in this way as long as the reservoir perturbations are sufficiently small.

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