- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Overcoming Individual Discrepancies, a Learning Model for Non-Invasive Blood Glucose Measurement
摘要： Non-invasive Glucose Measurement (NGM) technology makes great sense for the blood glucose management of patients with hyperglycemia or hypoglycemia. Individual Discrepancies (IDs), e.g., skin thickness and color, not only block the development of NGM, but also become the reason why NGM cannot be widely used. To solve this problem, our solution is designing an individual customized NGM model that can measure these discrepancies through multi-wavelength and tune parameters for glucose estimating. In this paper, an NGM prototype is designed, and a learning model for glucose estimating with automatically parameters tuning based on Independent Component Analysis (ICA) and Random Forest (RF) is presented. The clinic trial proves that the correlation coefficient between estimation and reference Blood Glucose Concentration (BGC) can reach 0.5 after merely 10 times of learning, and rise to 0.8 after about 60 times of learning.
关键词： Independent Component Analysis (ICA),random forest,non-invasive,blood glucose,diabetes
更新于2025-09-23 15:22:29
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Multiple Input Single Output Phase Retrieval
摘要： In this paper, we consider the problem of recovering the phase information of multiple sources from a mixed phaseless short-time Fourier transform measurement, which is called multiple input single output (MISO) phase retrieval problem. It is an inherently ill-posed problem due to the lack of the phase and mixing information, and the existing phase retrieval algorithms are not explicitly designed for this case. To address the MISO phase retrieval problem, a least-squares method coupled with an independent component analysis (ICA) algorithm is proposed for the case of sufficiently long window length. When these conditions are not met, an integrated algorithm is presented, which combines a gradient descent algorithm by minimizing a non-convex loss function with an ICA algorithm. Experimental evaluation has been conducted to show that under appropriate conditions the proposed algorithms can explicitly recover the signals, the phases of the signals, and the mixing matrix. In addition, the algorithm is robust to noise.
关键词： Short-time Fourier transform (STFT),Multiple input single output (MISO),Independent component analysis (ICA),Non-convex optimization,Phase retrieval
更新于2025-09-19 17:15:36
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Near-Field Radio Holography of Slant-Axis Terahertz Antennas
摘要： Principal component analysis (PCA) and independent component analysis (ICA) for radiated emissions from printed circuits are critically intercompared, revealing similarities and differences of the extracted components between both methods. The input data in this analysis are measured wideband complex-valued magnetic radiated and evanescent fields with quasi-Gaussian spatial distributions. PCA and ICA lead to similar maps of their components when considered as spatial eigenmodes, but independent components exhibit simpler field structure than principal components.
关键词： stochastic fields,principal component analysis (PCA),uncertainty quantification,Independent component analysis (ICA),radiated emissions
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Investigation of Accuracy of various STC Correction Procedures for I-V Characteristics of PV Modules Measured at Different Temperature and Irradiances
摘要： Principal component analysis (PCA) and independent component analysis (ICA) for radiated emissions from printed circuits are critically intercompared, revealing similarities and differences of the extracted components between both methods. The input data in this analysis are measured wideband complex-valued magnetic radiated and evanescent fields with quasi-Gaussian spatial distributions. PCA and ICA lead to similar maps of their components when considered as spatial eigenmodes, but independent components exhibit simpler field structure than principal components.
关键词： Independent component analysis (ICA),principal component analysis (PCA),radiated emissions,uncertainty quantification,stochastic fields
更新于2025-09-19 17:13:59