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arXiv 2024年

作者： Williams, Jan P. Kutz, J. Nathan Manohar, Krithika Department of Mechanical Engineering University of Washington SeattleWA United States Departments of Applied Mathematics and Electrical and Computer Engineering University of Washington SeattleWA United States

Model predictive control (MPC) is an industry standard control technique that iteratively solves an open-loop optimization problem to guide a system towards a desired state or trajectory. Consequently, an accurate forward model of system dynamics is critical for the efficacy of MPC and much recent work has been aimed at the use of neural networks to act as data-driven surrogate models to enable MPC. Perhaps the most common network architecture applied to this task is the recurrent neural network (RNN) due to its natural interpretation as a dynamical system. In this work, we assess the ability of RNN variants to both learn the dynamics of benchmark control systems and serve as surrogate models for MPC. We find that echo state networks (ESNs) have a variety of benefits over competing architectures, namely reductions in computational complexity, longer valid prediction times, and reductions in cost of the MPC objective function. © 2024, CC BY.

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PVBM: A Python Vasculature Biomarker Toolbox Based on Retinal Blood Vessel Segmentation 17th

PVBM: A Python Vasculature Biomarker Toolbox Based on Retin...

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17th European Conference on Computer Vision, ECCV 2022

作者： Fhima, Jonathan Eijgen, Jan Van Stalmans, Ingeborg Men, Yevgeniy Freiman, Moti Behar, Joachim A. Faculty of Biomedical Engineering Technion-IIT Haifa Israel Department of Applied Mathematics Technion-IIT Haifa Israel Research Group Ophthalmology Department of Neurosciences KU Leuven Leuven Belgium Department of Ophthalmology University Hospitals UZ Leuven Leuven Belgium The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering Technion-IIT Haifa Israel

ISBN: (纸本)9783031250651

Introduction: Blood vessels can be non-invasively visualized from a digital fundus image (DFI). Several studies have shown an association between cardiovascular risk and vascular features obtained from DFI. Recent advances in computer vision and image segmentation enable automatising DFI blood vessel segmentation. There is a need for a resource that can automatically compute digital vasculature biomarkers (VBM) from these segmented DFI. Methods: In this paper, we introduce a Python Vasculature BioMarker toolbox, denoted PVBM. A total of 11 VBMs were implemented. In particular, we introduce new algorithmic methods to estimate tortuosity and branching angles. Using PVBM, and as a proof of usability, we analyze geometric vascular differences between glaucomatous patients and healthy controls. Results: We built a fully automated vasculature biomarker toolbox based on DFI segmentations and provided a proof of usability to characterize the vascular changes in glaucoma. For arterioles and venules, all biomarkers were significant and lower in glaucoma patients compared to healthy controls except for tortuosity, venular singularity length and venular branching angles. Conclusion: We have automated the computation of 11 VBMs from retinal blood vessel segmentation. The PVBM toolbox is made open source under a GNU GPL 3 license and is available on *** (following publication). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image segmentation

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Active Tuning of the Microresonator Coupling Condition with Coupled Rings

Active Tuning of the Microresonator Coupling Condition with ...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Yun Zhao Karl J. McNulty Michal Lipson Alexander L. Gaeta Department of Applied Physics and Applied Mathematics Columbia University New York NY USA Department of Electrical Engineering Columbia University New York NY USA

We demonstrate a novel approach to actively and continuously tune the coupling condition of microresonators. Our approach allows for wavelength-dependent coupling and dispersion modification after fabrication.

ISBN: (纸本)9781957171258

关键词： Dispersion Extinction ratios Field enhancement Microresonators Photons Resonance

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Efficient Algorithm Design of Dynamic Spectrum Access by Whittle Index

arXiv

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arXiv 2024年

作者： Liu, Keqin Zhang, Yiying Ding, Zhi Department of Financial and Actuarial Mathematics Xi'an Jiaotong-Liverpool University Suzhou China National Center for Applied Mathematics Nanjing China Department of Electrical and Computer Engineering University of California Davis United States

This study addresses the dynamic spectrum access problem in a wireless sub-network that shares channels with a parent network. We approach the sequential channel allocation problem using a restless multi-armed bandits (RMAB) framework. Our objective is to maximize the expected discounted return over an infinite horizon while minimizing interference to the parent network caused by shared channels with the sub-network. Due to the unavailability of direct observations of the true channel state, we leverage the channel quality indicator (CQI) feedback provided by users. However, the RMAB problem is widely acknowledged as PSPACE-hard even for finite-state models. To overcome this challenge, we propose a closed-form channel index function using an iterative online approximation method to approximate the well-known Whittle index policy, which offers a low-complexity solution for ranking the available channels that has an infinite state space. Through extensive numerical simulation experiments, we demonstrate the superior performance and robustness of our proposed algorithm. © 2024, CC BY.

关键词： Iterative methods

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Compute-first optical detection for noise-resilient visual perception

arXiv

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arXiv 2024年

作者： Kim, Jungmin Yu, Nanfang Yu, Zongfu Department of Electrical and Computer Engineering University of Wisconsin-Madison MadisonWI53706 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States

In the context of visual perception, the optical signal from a scene is transferred into the electronic domain by detectors in the form of image data, which are then processed for the extraction of visual information. In noisy and weak-signal environments such as thermal imaging for night vision applications, however, the performance of neural computing tasks faces a significant bottleneck due to the inherent degradation of data quality upon noisy detection. Here, we propose a concept of optical signal processing before detection to address this issue. We demonstrate that spatially redistributing optical signals through a properly designed linear transformer can enhance the detection noise resilience of visual perception tasks, as benchmarked with the MNIST classification. Our idea is supported by a quantitative analysis detailing the relationship between signal concentration and noise robustness, as well as its practical implementation in an incoherent imaging system. This compute-first detection scheme can pave the way for advancing infrared machine vision technologies widely used for industrial and defense applications. © 2024, CC BY.

关键词： Infrared imaging

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Joint Task Offloading and Resource Allocation in Heterogeneous Edge Environments

Joint Task Offloading and Resource Allocation in Heterogeneo...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Yu Liu Yingling Mao Zhenhua Liu Fan Ye Yuanyuan Yang Department of Electrical and Computer Engineering Stony Brook University USA Department of Applied Mathematics and Statistics Stony Brook University USA

Mobile edge computing is becoming one of the ubiquitous computing paradigms to support applications requiring low latency and high computing capability. FPGA-based reconfigurable accelerators have high energy efficiency and low latency compared to general-purpose servers. Therefore, it is natural to incorporate reconfigurable accelerators in mobile edge computing systems. This paper formulates and studies the problem of joint task offloading, access point selection, and resource allocation in heterogeneous edge environments for latency minimization. Due to the heterogeneity in edge computing devices and the coupling between offloading, access point selection, and resource allocation decisions, it is challenging to optimize over them simultaneously. We decomposed the proposed problem into two disjoint subproblems and developed algorithms for them. The first subproblem is to jointly determine offloading and computing resource allocation decisions and is NP-hard, where we developed an algorithm based on semidefinite relaxation. The second subproblem is to jointly determine access point selection and communication resource allocation decisions, where we proposed an algorithm with a provable approximation ratio of 2.62. We conducted extensive numerical simulations to evaluate the proposed algorithms. Results highlighted that the proposed algorithms outperformed baselines and were near-optimal over a wide range of settings.

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Nonlinear Self-injection Locking for All-Passive Laser Stabilization Beyond the Schawlow-Townes Limit

Nonlinear Self-injection Locking for All-Passive Laser Stabi...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Andrew M. Bishop Alexander L. Gaeta Department of Applied Physics and Applied Mathematics Columbia University New York NY USA Department of Electrical Engineering Columbia University New York NY USA

We propose a method for laser stabilization and phase-noise reduction using nonlinear feedback in which a gain-narrowed signal mode of a nonlinear oscillator is re-injected back into the pump laser. We show a proof-of... 详细信息

ISBN: (纸本)9781957171258

关键词： Brillouin scattering Distributed feedback lasers Frequency doubled lasers Laser stabilization Phase modulation Phase noise

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Integrated, Compact, and Tunable Band-Interleaving of a Kerr Comb Source

Integrated, Compact, and Tunable Band-Interleaving of a Kerr...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Songli Wang Asher Novick Anthony Rizzo Robert Parsons Swarnav Sanyal Karl Jacob McNulty Bok Young Kim Yoshitomo Okawachi Yuyang Wang Alexander Gaeta Michal Lipson Keren Bergman Department of Electrical Engineering Columbia University New York NY USA Department of Applied Physics and Applied Mathematics Columbia University New York NY USA

We demonstrate band-interleaving of a Kerr comb via a wide-FSR dual-ring RAMZI filter. A sharp filter roll-off of 63.6dB/nm is measured with a total functional bandwidth >36nm with broadband crosstalk suppression ... 详细信息

ISBN: (纸本)9781957171258

关键词： Crosstalk Dense wavelength division multiplexing Frequency combs Grating couplers Optical directional couplers Ring resonators

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Reduced Order Modeling with Shallow Recurrent Decoder Networks

arXiv

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arXiv 2025年

作者： Tomasetto, Matteo Williams, Jan P. Braghin, Francesco Manzoni, Andrea Kutz, J. Nathan Department of Mechanical Engineering Politecnico di Milano Milano Italy Department of Mechanical Engineering University of Washington SeattleWA United States MOX Department of Mathematics Politecnico di Milano Milano Italy Department of Applied Mathematics and Electrical and Computer Engineering University of Washington SeattleWA United States

Reduced Order Modeling is of paramount importance for efficiently inferring high-dimensional spatio-temporal fields in parametric contexts, enabling computationally tractable parametric analyses, uncertainty quantification and control. However, conventional dimensionality reduction techniques are typically limited to known and constant parameters, inefficient for nonlinear and chaotic dynamics, and uninformed to the actual system behavior. In this work, we propose sensor-driven SHallow REcurrent Decoder networks for Reduced Order Modeling (SHRED-ROM). Specifically, we consider the composition of a long short-term memory network, which encodes the temporal dynamics of limited sensor data in multiple scenarios, and a shallow decoder, which reconstructs the corresponding high-dimensional states. SHRED-ROM is a robust decoding-only strategy that circumvents the numerically unstable approximation of an inverse which is required by encoding-decoding schemes. To enhance computational efficiency and memory usage, the full-order state snapshots are reduced by, e.g., proper orthogonal decomposition, allowing for compressive training of the networks with minimal hyperparameter tuning. Through applications on chaotic and nonlinear fluid dynamics, we show that SHRED-ROM (i) accurately reconstructs the state dynamics for new parameter values starting from limited fixed or mobile sensors, independently on sensor placement, (ii) can cope with both physical, geometrical and time-dependent parametric dependencies, while being agnostic to their actual values, (iii) can accurately estimate unknown parameters, and (iv) can deal with different data sources, such as high-fidelity simulations, coupled fields and videos. Copyright © 2025, The Authors. All rights reserved.

关键词： Decoding

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Resonance for analog recurrent neural network

Resonance for analog recurrent neural network

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Conference on Lasers and Electro-Optics (CLEO)

作者： Yurui Qu Ming Zhou Erfan Khoram Nanfang Yu Zongfu Yu Department of Electrical and Computer Engineering University of Wisconsin Madison WI USA Department of Applied Physics and Applied Mathematics Columbia University New York NY USA

ISBN: (纸本)9781957171258

Resonance, as a ubiquitous feature across many wave systems, is a natural candidate for analog computing in temporal signals. We demonstrate that resonance can be used to construct stable and scalable recurrent neural networks. By including resonators with different lifetimes, the computing system develops both short-term and long-term memories simultaneously.

关键词： Neural networks Optical resonators Resonance Waveguides Whispering gallery modes

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