Article
Physics, Multidisciplinary
Duolan, Linying Xiang, Guanrong Chen
Summary: In this article, the framework of master stability function is extended to stochastic complex networks with time-delayed coupling. The effects of noise, time delay, and their interactions on network synchronization are explored. It is found that increasing the noise intensity can enhance network synchronizability when there is time-delayed coupling and noise diffusion through all state variables of nodes; otherwise, noise can have either positive or negative effects. In stochastic networks, large time delays cause desynchronization. These findings provide valuable insights for designing optimal complex networks in practical applications.
Article
Computer Science, Artificial Intelligence
Hao Zhang, Zhigang Zeng
Summary: This article investigates the master-slave synchronization of reaction-diffusion neural networks (RDNNs) with nondifferentiable delay using the adaptive control method. The article first designs centralized and decentralized adaptive controllers with state coupling, and proposes a new analytical method to prove the convergence of the adaptively controlled error system with general delay. It then introduces a spatial coupling with adaptive gains dependent on the diffusion information to achieve the master-slave synchronization of delayed RDNNs. Numerical examples demonstrate the effectiveness of the proposed adaptive controllers, which have wider applications even with unknown network parameters and nonsmooth delay.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Neurosciences
Mojtaba Madadi Asl, Saeideh Ramezani Akbarabadi
Summary: Synchronization and synaptic plasticity play important roles in learning and memory, but they are affected by transmission delays and spike-timing-dependent plasticity (STDP), leading to changes in the activity and connectivity patterns of neurons.
COGNITIVE NEURODYNAMICS
(2023)
Article
Computer Science, Information Systems
Hongguang Fan, Yi Zhao
Summary: This paper investigates the adaptive cluster synchronization of fractional-order complex networks with internal and coupling delays, as well as time-varying disturbances using fractional-order hybrid controllers. The results extend previous literature by providing sufficient conditions for cluster synchronization of two kinds of fractional-order nonlinear dynamical systems. Numerical simulations confirm the effectiveness of the theoretical results.
Article
Computer Science, Interdisciplinary Applications
Yi Wang, Zhaoyan Wu
Summary: This paper investigates cluster synchronization for fractional-order complex network with nondelay and delay coupling. Both static and adaptive control schemes are adopted to design effective controllers based on the stability theory of fractional-order systems and the properties of fractional derivative. The sufficient condition for achieving cluster synchronization about static controllers is provided. In the adaptive controllers, the feedback gains can adjust themselves to the needed values according to updating laws. Numerical simulations demonstrate the correctness of the obtained results.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2022)
Article
Chemistry, Multidisciplinary
Tao Wang, Paula Angulo-Portugal, Alejandro Berdonces-Layunta, Andrej Jancarik, Andre Gourdon, Jan Holec, Manish Kumar, Diego Soler, Pavel Jelinek, David Casanova, Martina Corso, Dimas G. de Oteyza, Jan Patrick Calupitan
Summary: The coupling of a sterically demanded pentacene derivative on Au(111) into fused dimers connected by non-benzenoid rings was studied using high-resolution scanning tunneling microscopy/spectroscopy and density functional theory. The diradical character of the products was tuned by modifying the coupling section, with the antiaromaticity of cyclobutadiene and its position within the structure playing a significant role. Understanding these structure-property relationships is crucial for designing new complex and functional molecular structures.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Multidisciplinary Sciences
Huawei Fan, Ling-Wei Kong, Xingang Wang, Alan Hastings, Ying-Cheng Lai
Summary: Transient synchronization behavior is discovered in spatial ecological networks, where different patterns of complete synchronization coexist and switch randomly due to intrinsic instability or noise. This phenomenon, known as 'synchronization within synchronization,' is determined by network symmetry and follows an algebraic scaling law for transient time distribution with a divergent average transient lifetime. Symmetry considerations can also be used to explain counterintuitive synchronization behaviors in ecological networks.
NATIONAL SCIENCE REVIEW
(2021)
Article
Multidisciplinary Sciences
David S. Glass, Xiaofan Jin, Ingmar H. Riedel-Kruse
Summary: Studying biological networks through delay differential equation models provides important insights, such as parameter reduction, analytical relationships between ODE and DDE models, phase space for autoregulation, behaviors of feedforward loops, and a unified Hill-function logic framework. Explicit-delay modeling simplifies the phenomenology of biological networks and may aid in discovering new functional motifs.
NATURE COMMUNICATIONS
(2021)
Article
Physics, Multidisciplinary
Xiaoming Liang, Chao Fang, Xiyun Zhang, Huaping Lue
Summary: The three-node feedforward motif is found to act as a weak signal amplifier. By changing the motif's unidirectional couplings to bidirectional couplings, a small asymmetric coupling can lead to double resonant signal response. The analytical description of the double resonance matches the numerical findings.
Article
Physics, Multidisciplinary
Xiangdong Liu
Summary: This letter discusses the collective dynamics of heterogeneous phase oscillator networks encoded by simplexes under coupling strength symmetry breaking. The findings suggest that proper symmetry breaking can enhance the synchronization capability of the system, while strong symmetry breaking leads to significant desynchronization behavior. The optimal intrinsic frequency assignment scheme is determined based on the spectral decomposition of the composite Laplace matrix of the underlying network.
Article
Computer Science, Artificial Intelligence
Xiaoyu Zhang, Chuandong Li, Hongfei Li, Jing Xu
Summary: This article addresses the synchronization issue for coupled neural networks with mixed couplings using delayed impulsive control. Novel delayed impulsive differential inequalities involving distributed-delay-dependent impulses are proposed, and sufficient criteria and distributed-delay-dependent impulsive controller are derived for CNNs with different topologies. With the use of matrix decomposition techniques, low-dimensional criteria suitable for large scale CNN applications are set out, and the theoretical results are validated through numerical examples involving various cases.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Immunology
Michael Reth
Summary: The cryo-EM structures of TCR and BCR provide molecular details of their interactions but do not reveal the signaling mechanisms. Understanding these mechanisms is crucial for designing effective vaccines.
FRONTIERS IN IMMUNOLOGY
(2023)
Article
Physics, Multidisciplinary
Hai Lin, Jingcheng Wang
Summary: This article investigates the pinning control problem for complex networks with time-varying outer and nonlinear multiple time-varying delay coupling. It provides appropriate pinning feedback controllers and synchronization criteria based on Lyapunov function theory. The study also examines the influence of the boundary of the time-varying outer coupling on synchronization, and extends the theoretical results to complex networks with general time-varying delay coupling.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Mathematics, Applied
I. A. Shepelev, S. S. Muni, T. E. Vadivasova
Summary: This study investigates the synchronization effects in a heterogeneous two-layer network with attractive and repulsive inter-layer couplings, revealing the competition and mutual impact between two different types of couplings.
Article
Mathematics, Interdisciplinary Applications
Shilong Zhang, Feifei Du, Diyi Chen
Summary: This article investigates quasi-synchronization for a class of fractional-order delayed neural networks. By introducing a new fractional-order differential inequality and designing an adaptive controller, an effective criterion is proposed to ensure the quasi-synchronization.
FRACTAL AND FRACTIONAL
(2023)
Editorial Material
Multidisciplinary Sciences
Ingo Fischer, Daniel J. Gauthier
Article
Multidisciplinary Sciences
Apostolos Argyris, Janek Schwind, Ingo Fischer
Summary: Despite the conceptual simplicity of hardware reservoir computing, the implementation schemes still face versatile challenges. Researchers propose a clock-free method for generating repetitive patterns and using them as masking sequences to reduce instrumentation requirements. By studying a semiconductor laser system, they successfully apply these patterns to a nonlinear time-series prediction task, making minor compromises while significantly improving the efficiency of the system.
SCIENTIFIC REPORTS
(2021)
Article
Biochemical Research Methods
Aref Pariz, Ingo Fischer, Alireza Valizadeh, Claudio Mirasso
Summary: This study focuses on the role of connection delay and the oscillation frequency of neural populations in signal transmission within brain networks. The research shows that these parameters have a significant impact on the effective connectivity of neural networks, influencing the quality of information transfer.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Florian Stelzer, Andre Roehm, Raul Vicente, Ingo Fischer, Serhiy Yanchuk
Summary: The method folds a deep neural network into a single neuron with multiple time-delayed feedback loops, adapting the network's connection weights and showing promising performance, which is also relevant for new hardware implementations and applications.
NATURE COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Irene Estebanez, Shi Li, Janek Schwind, Ingo Fischer, Stephan Pachnicke, Apostolos Argyris
Summary: Analog photonic computing has been proposed and tested as an alternative approach for data recovery in fiber transmission systems. This study demonstrates the effectiveness of internal fading memory in photonic reservoir computing, highlighting its dependence on signal properties. It also compares data recovery performances between reservoir computing and extreme learning machine fiber-based configurations, showing equivalent results and the advantage of simplified system and increased computation speed with the latter method.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2022)
Article
Optics
Xavier Porte, Daniel Brunner, Ingo Fischer, Miguel C. Soriano
Summary: This paper examines the emission properties of semiconductor lasers under external perturbations, focusing on the impact of delayed optical feedback. The authors present an overview of the main dynamical features in these lasers and discuss experimental methods for characterizing these features.
Article
Physics, Multidisciplinary
Anti Ingel, Abdullah Makkeh, Oriol Corcoll, Raul Vicente
Summary: In this study, we introduce an algorithm for computing the level of autonomy of an agent using an information-theoretic formulation. We use the partial information decomposition framework to monitor the autonomy level and environment internalization of reinforcement learning agents. Our experiments show strong correlations between specific PID terms and the obtained reward, as well as the agent's behavior in response to perturbations in the observations.
Article
Materials Science, Multidisciplinary
Silvia Ortin, Miguel C. Soriano, Ingo Fischer, Claudio R. Mirasso, Apostolos Argyris
Summary: Multimode fibers are widely used in short-range communication and optical imaging, and have recently been considered for optical computing. This study mimics the dendritic structure of real neurons and utilizes the spatial modes and spatio-temporal transformation of multimode fibers for information processing. Through numerical simulations, we demonstrate the application of a few-mode, step-index fiber as a linear computing element in a high-speed spatio-temporal coincidence detector and evaluate its performance as a linear classifier in classification tasks.
OPTICAL MATERIALS EXPRESS
(2022)
Article
Mathematics, Applied
Vladimir V. Klinshov, Otti D'Huys
Summary: This paper investigates the effects of two types of noise on the dynamics of an oscillatory system with pulse delayed feedback. The study finds that the robustness of the system differs significantly depending on the type of noise, and that phase noise drives the system towards higher frequencies while stochastic delays do not.
Article
Mathematics, Applied
Daniel J. Gauthier, Ingo Fischer, Andre Rohm
Summary: Reservoir computing is a machine learning approach that can generate a surrogate model of a dynamical system. The next-generation reservoir computing approach simplifies training further and exhibits higher accuracy in predicting attractor characteristics compared to traditional approaches.
Article
Optics
Moritz Pfluger, Daniel Brunner, Tobias Heuser, James A. Lott, Stephan Reitzenstein, Ingo Fischer
Summary: In this article, we demonstrate the construction of the largest network of optically coupled semiconductor lasers reported so far by using diffractive optics in an external cavity to couple vertical-cavity surface-emitting lasers (VCSELs). We successfully align and lock 22 out of 25 lasers to an external drive laser, and show significant interaction between the lasers of the array. Our VCSEL network, with its high homogeneity, strong interaction, and scalability, serves as a promising platform for experimental investigations of complex systems and has direct applications as a photonic neural network.
Article
Optics
Irene Estebanez, Apostolos Argyris, Ingo Fischer
Summary: Time delay reservoir computing using semiconductor lasers is a promising photonic analog approach for information processing. By adjusting the level of optical injection, the response bandwidth of the lasers can be tuned. Experimental results show that the system can operate with a sampling time as small as 11.72 ps without sacrificing computational performance.
Article
Physics, Multidisciplinary
Silvia Ortin, Miguel C. Soriano, Christian Tetzlaff, Florentin Woergoetter, Ingo Fischer, Claudio R. Mirasso, Apostolos Argyris
Summary: The implementation of machine learning concepts using optoelectronic and photonic components is rapidly advancing. The researchers use optical dendritic structures to transfer neurobiological principles to photonics computation. The presented optical fiber-based dendritic structure is an efficient hardware platform for ultra-fast control.
FRONTIERS IN PHYSICS
(2023)
Article
Physics, Fluids & Plasmas
Mirko Goldmann, Claudio R. Mirasso, Ingo Fischer, Miguel C. Soriano
Summary: We propose scalable neural networks that can handle translational symmetries in dynamical systems and infer high-dimensional dynamics for different system sizes. By training the networks to predict dynamics for a single size and then driving them with their own predictions, we show that the complex dynamics for larger or smaller system sizes can be accurately predicted. The network learns from a single example and leverages symmetry properties to infer entire bifurcation diagrams.
Article
Mathematics, Applied
Matthias Wolfrum, Serhiy Yanchuk, Otti D'Huys
Summary: In this study, the mechanisms for the appearance of multiple coexisting partially locked states in the Kuramoto-Sakaguchi system were fully analytically explained, along with the stability characteristics of these states and the role of the Sakaguchi phase lag parameter under different delay conditions.
SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS
(2022)
