Performance Analysis of Reconstruction Techniques for Frequency-Domain Optical-Coherence Tomography

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Linear-Quadratic-Gaussian (LQG) control is a fundamental control paradigm that is studied in various fields such as engineering, computer science, economics, and neuroscience. It involves controlling a system with linear dynamics and imperfect observations ...

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WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

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This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noise-canceling headphones. The IoT microphones forward ambient noise ...

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A Multimodal Dataset for Automatic Edge-AI Cough Detection

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Counting the number of times a patient coughs per day is an essential biomarker in determining treatment efficacy for novel antitussive therapies and personalizing patient care. Automatic cough counting tools must provide accurate information, while runnin ...

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A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

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We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

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Exploring the effectiveness of using internal CNC system signals for chatter detection in milling process

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Chatter is a harmful self-excited vibration that commonly occurs during milling processes. Data -driven chatter detection and prediction is critical to achieve high surface quality and process efficiency. Most existing chatter detection approaches are base ...

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An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

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Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...

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Spatially multiplexed single-molecule translocations through a nanopore at controlled speeds

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In current nanopore-based label-free single-molecule sensing technologies, stochastic processes influence the selection of translocating molecule, translocation rate and translocation velocity. As a result, single-molecule translocations are challenging to ...

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Engineering Hydrogel-coated Neural Interfaces for Chronic Deep Brain Recording

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Implanted brain electrodes provide a unique way of electrically interfacing with individual neurons in vivo. However, chronic recording or stimulating capabilities of neural implants are often impaired by a strong immune response resulting in a fibrous sca ...

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Quantization for Decentralized Learning Under Subspace Constraints

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In this article, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the minimizers across the network to lie in low-dimensional subspaces. This constrained fo ...

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Disentangling 1/f noise from confined ion dynamics

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Ion transport through biological and solid-state nanochannels is known to be a highly noisy process. The power spectrum of current fluctuations is empirically known to scale like the inverse of frequency, following the long-standing yet poorly understood H ...

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Functional data analysis with rough sample paths?

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Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

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Electronic readout of DNA amplification in nanoliter chambers. Strategies towards highly parallel semiconductor-based nucleic acid amplification testing

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