Article
Computer Science, Interdisciplinary Applications
Toni Cvitanic, Shreyes N. Melkote
Summary: In order to achieve higher position accuracy for industrial robots used in precision manufacturing tasks, closed-loop feedback control with external sensors is commonly employed. Existing simplistic models require manual tuning of closed-loop controller gains due to their shortcomings, but by identifying missing components in these models and establishing a new data-driven method, controller gains can be efficiently determined through simulation. This new model-based method was experimentally evaluated on a six degree-of-freedom industrial manipulator, demonstrating the ability to achieve closed-loop stability without iterative gain-tuning experiments.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Artificial Intelligence
Man Zhou, Jie Huang, Danfeng Hong, Feng Zhao, Chongyi Li, Jocelyn Chanussot
Summary: This paper proposes a closed-loop scheme that learns both the pan-sharpening and its corresponding degradation process simultaneously to regulate the solution space. A specific multiscale high-frequency texture extraction module is also designed to strengthen the algorithm. Experimental results demonstrate the effectiveness of the proposed algorithm.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Industrial
Jie Wei, Weiyu Chen, Guoxin Liu
Summary: The study finds that in a closed-loop supply chain, the manufacturer's optimal integration strategy is to integrate the retailer and one collector, especially when collection competition is intense. This can improve the overall collection rate and maximize the surplus profit of the integration strategy.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Neurosciences
Simon Ruch, Flavio Jean Schmidig, Leona Knuesel, Katharina Henke
Summary: Slow-wave sleep is a crucial stage for the body's recovery, characterized by slow oscillations in the scalp EEG. Studies have shown that closed-loop sensory stimulation targeting the UP-states of slow oscillations can enhance sleep depth and promote sleep's recuperative functions. However, conventional closed-loop stimulation algorithms may overlook the individual differences in slow oscillations on the scalp. Researchers have proposed a novel EEG-based algorithm, TOPOSO, that can accurately detect and target specific cerebral origins of local slow oscillations.
Article
Acoustics
Zeqiang Zhang, Ming Wu, Lan Yin, Chen Gong, Jiajie Wang, Shuang Zhou, Jun Yang
Summary: This paper proposes a design method that combines the remote microphone method with a robust fixed feedback controller to achieve active noise control in a headrest. The design objectives consider noise reduction performance, waterbed lift, and robustness against plant perturbations. Particle swarm optimization algorithm is employed to efficiently generate the feedback controller. Simulations and real-time experiments demonstrate the superior noise reduction performance and robust stability of the designed controller in attenuating broadband disturbances in a vehicle.
Article
Engineering, Electrical & Electronic
Baktash Behmanesh, Pietro Andreani
Summary: The expression of the loop gain in a circuit with one or more feedback loops is derived using transfer functions obtained through AC analysis. This method, while suitable for analog circuit simulator environments, does not require approximations or assumptions on the nature of the loop or the impedances.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Engineering, Electrical & Electronic
Jianhui Ma, Qiang Li, Zilong Liu, Linsong Du, Hongyang Chen, Nirwan Ansari
Summary: This paper presents a novel active anti-jamming (AAJ) scheme that enhances the communication quality between a transmitter node and receiver node under adversarial electronic attacks. By re-modulating the jamming signals using a programmable-gain amplifier, the proposed scheme allows reliable communication even under strong and broadband jamming.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Review
Neurosciences
Farhad Farkhondeh Tale Navi, Soomaayeh Heysieattalab, Dhakshin S. Ramanathan, Mohammad Reza Raoufy, Mohammad Ali Nazari
Summary: This review provides an overview of closed-loop neuroscience and closed-loop neuromodulation, discussing their applications, theories, and methods, as well as their potential for improving mental health and well-being.
Article
Optics
Nikita Tarasov, Leonid A. Melnikov, Ilya D. Vatnik, Yulia A. Mazhirina, Dmitriy V. Churkin
Summary: In this study, a pulsed operation in a random fiber laser operation via self-gain-switching was experimentally demonstrated, showing pulses with low timing jitter and high average output power. The repetition rate was shown to switch abruptly while varying the pump power, and a simple formula for oscillation frequencies was introduced.
Article
Biology
Laura B. Naumann, Joram Keijser, Henning Sprekeler
Summary: This study investigates the establishment of context-invariant representations through feedback processing. The results show that feedback-modulated feedforward neural networks can dynamically generate invariant sensory representations, rather than on the level of individual neurons. This invariance is achieved by dynamically reorienting the manifold of neural activity and maintaining an invariant neural subspace at the population level.
Article
Computer Science, Information Systems
Lekshmy Sudha Kumari, Abbas Z. Kouzani
Summary: This paper presents a tetherless and miniaturized closed-loop optogenetic brain stimulation device for laboratory mice, which can sense biomarkers related to major depressive disorder and provide feedback to control the stimulation. The device is designed to address the issue of hindering the free movement of the animals caused by tethered devices in previous experiments.
Article
Engineering, Biomedical
Shuxun Dong, Jiaqing Yan, Zhenyu Xie, Yi Yuan, Hui Ji
Summary: The modulation effect of closed-loop transcranial ultrasound stimulation on theta rhythm depends on the stimulation mode and duration, showing that with peak stimulation, the relative change in amplitude and absolute power of theta rhythm decreases with the number of stimulation trials. Additionally, the relative change in amplitude and absolute power of theta rhythm increases nonlinearly with the stimulation duration under peak stimulation. This suggests that TUS has the potential to precisely modulate theta rhythm-related neural activity.
JOURNAL OF NEURAL ENGINEERING
(2022)
Article
Optics
Bo Yang, Jiwen Yu, Hao Chi, Shuna Yang, Yanrong Zhai, Jun Ou
Summary: In this paper, a polarization multiplexed active mode-locking optoelectronic oscillator (AML-OEO) based on a single dual-polarization binary phase-shift keying (DP-BPSK) modulator is proposed and experimentally demonstrated for generating frequency tunable dual-band microwave pulse signals. The system divides the AML-OEO into two loops with polarization demultiplexing, allowing independent adjustment of the carrier frequency and pulse repetition frequency (PRF) of the dual-band microwave pulses. Experimental results show that the system can generate microwave pulses with different PRFs and the carrier frequency can be tuned within a certain range.
Article
Engineering, Aerospace
Feng Deng, Shenghua Zhang, Ning Qin
Summary: In this paper, a closed-loop control using an active shock control bump (SCB) has been proposed to suppress the buffet on a supercritical airfoil flying at transonic speeds. The control law is designed based on the lift coefficient as the feedback signal and the bump height as the control variable. Numerical simulations show that the buffet can be effectively suppressed by optimizing the control law parameters, namely the gain and the delay time. The active SCB has advantages over the reference active trailing edge flap, including less sensitivity to control law parameters and a shorter response time.
Article
Optics
Li Zhang, Ana Gabriela Correa-Mena, Zhisheng Yang, Florian Sauser, Sebastien Le Floch, Luc Thevenaz
Summary: This closed-loop servo control system provides real-time measurement without postprocessing in Brillouin optical time-domain analysis (BOTDA). It offers fast measurement speed, a large measurement range, high spatial resolution, and is suitable for field applications in harsh environments.
Article
Neurosciences
Erin Munro Krull, Shuzo Sakata, Taro Toyoizumi
FRONTIERS IN NEUROSCIENCE
(2019)
Article
Mathematical & Computational Biology
James Humble, Kazuhiro Hiratsuka, Haruo Kasai, Taro Toyoizumi
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2019)
Article
Multidisciplinary Sciences
Roberto Legaspi, Taro Toyoizumi
NATURE COMMUNICATIONS
(2019)
Review
Behavioral Sciences
Roberto Legaspi, Zhengqi He, Taro Toyoizumi
CURRENT OPINION IN BEHAVIORAL SCIENCES
(2019)
Article
Physics, Multidisciplinary
Lukasz Kusmierz, Shun Ogawa, Taro Toyoizumi
PHYSICAL REVIEW LETTERS
(2020)
Letter
Multidisciplinary Sciences
Lukasz Kusmierz, Taro Toyoizumi
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Biochemical Research Methods
Yoshiki Ito, Taro Toyoizumi
Summary: The study demonstrates that traveling waves can facilitate the learning of synaptic network paths, especially when combined with a reward-dependent local synaptic plasticity rule. This mechanism helps improve brain function and accelerate the learning process.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Review
Neurosciences
Haruo Kasai, Noam E. Ziv, Hitoshi Okazaki, Sho Yagishita, Taro Toyoizumi
Summary: Dendritic spines in the brain embody algorithms for learning and adaptation, with their dynamics influenced by activity, input, and neuromodulatory factors. Disruptions in these dynamics may contribute to mental disorders, highlighting potential relevance to future developments in artificial intelligence.
NATURE REVIEWS NEUROSCIENCE
(2021)
Article
Neurosciences
Genki Shimizu, Kensuke Yoshida, Haruo Kasai, Taro Toyoizumi
Summary: This article reviews previous computational studies on the roles of intrinsic synaptic dynamics, suggesting that neuronal networks may maintain stable performance in their presence. The authors also hypothesize that intrinsic dynamics could enhance information processing in the brain beyond mere noise.
CURRENT OPINION IN NEUROBIOLOGY
(2021)
Editorial Material
Multidisciplinary Sciences
Taro Toyoizumi
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Multidisciplinary Sciences
Kensuke Yoshida, Taro Toyoizumi
Summary: This study provides a unified explanation for the slow waves and plasticity during NREM sleep through an optimal synaptic plasticity theory in a cortical neuron model. The model suggests that the optimal plasticity biases towards depression as the baseline firing rate increases, explaining the observed distinct STDP. Additionally, the model explains how global and local slow waves potentiate and depress synapses, respectively, if the background firing rate of excitatory neurons decreases with the spatial scale of waves as predicted by the model.
Article
Multidisciplinary Sciences
Kensuke Yoshida, Taro Toyoizumi
Summary: Research has found that slow waves during non-rapid eye movement sleep reflect the up and down states of cortical neurons, and global and local slow waves promote memory consolidation and forgetting. The study also reveals the contribution of different spike-timing-dependent plasticity rules to neural information coding and memory reorganization.
Article
Physics, Multidisciplinary
Francesco Fumarola, Zhengqi He, Lukasz Kusmierz, Taro Toyoizumi
Summary: In experiments on free recall, not all memory retrievals are reported. This study shows that the statistics of unreported retrievals can be estimated through the analysis of inter-response times. Delayed recall due to unreported retrievals emerges in different situations, and a stochastic process can be used to model these effects.
PHYSICAL REVIEW RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Takuya Isomura, Taro Toyoizumi
Summary: Predicting future inputs in an unseen time series using machine learning is challenging, but a new unsupervised learning scheme called predictive principal component analysis (PredPCA) can effectively extract informative components with low computational cost. PredPCA demonstrates global convergence and can asymptotically identify hidden states, system parameters, and dimensionalities of nonlinear generative processes. It reliably predicts future outcomes of previously unseen test input data, making it a desirable option for neuromorphic hardware due to its simple architecture and low computational cost.
NATURE MACHINE INTELLIGENCE
(2021)
Article
Physics, Fluids & Plasmas
Lukasz Kusmierz, Taro Toyoizumi