- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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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) - An Assessment of Perovskite Solar Cells for Low-Intensity-Low-Temperature (LILT) Space Missions
摘要： We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool widely used in array signal processing and finite-rate-of-innovation (FRI) sampling. The proposed algorithm can reconstruct spatial samples. For large , this sampling requirement improves over previously known FRI sampling schemes on the sphere by a factor of four. We showcase the versatility of the proposed algorithm by applying it to three problems: 1) sampling diffusion processes induced by localized sources on the sphere, 2) shot noise removal, and 3) sound source localization (SSL) by a spherical microphone array. In particular, we show how SSL can be reformulated as a spherical sparse sampling problem.
关键词： sparse sampling,spherical harmonics,finite rate of innovation,sphere,Annihilation filter,diffusion sampling,shot noise removal,sound source localization
更新于2025-09-19 17:13:59
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[IEEE 2019 44th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) - Paris, France (2019.9.1-2019.9.6)] 2019 44th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) - Terahertz 1-bit digital dynamic phase programmable metasurface based on AlGaN/GaN heterostructure
摘要： We consider diffusion fields induced by a finite number of spatially localized sources and address the problem of estimating these sources using spatiotemporal samples of the field obtained with a sensor network. Within this framework, we consider two different time evolutions: the case where the sources are instantaneous, as well as, the case where the sources decay exponentially in time after activation. We first derive novel exact inversion formulas, for both source distributions, through the use of Green's second theorem and a family of sensing functions to compute generalized field samples. These generalized samples can then be inverted using variations of existing algebraic methods such as Prony's method. Next, we develop a novel and robust reconstruction method for diffusion fields by properly extending these formulas to operate on the spatiotemporal samples of the field. Finally, we present numerical results using both synthetic and real data to verify the algorithms proposed herein.
关键词： Prony's method,Spatiotemporal sampling,sensor networks,finite rate of innovation (FRI),diffusion fields
更新于2025-09-19 17:13:59
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[IEEE 2019 International Conference on ENERGY and ENVIRONMENT (CIEM) - Timisoara, Romania (2019.10.17-2019.10.18)] 2019 International Conference on ENERGY and ENVIRONMENT (CIEM) - Interharmonic and Harmonic Steady-State Computation of a Grid-Tied Photovoltaic System
摘要： We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool widely used in array signal processing and finite-rate-of-innovation (FRI) sampling. The proposed algorithm can reconstruct spatial samples. For large, this sampling requirement improves over previously known FRI sampling schemes on the sphere by a factor of four. We showcase the versatility of the proposed algorithm by applying it to three problems: 1) sampling diffusion processes induced by localized sources on the sphere, 2) shot noise removal, and 3) sound source localization (SSL) by a spherical microphone array. In particular, we show how SSL can be reformulated as a spherical sparse sampling problem.
关键词： sparse sampling,spherical harmonics,finite rate of innovation,sphere,Annihilation filter,diffusion sampling,shot noise removal,sound source localization
更新于2025-09-19 17:13:59