Robust identification from partial frequency data
作者： L. Baratchart , J. Leblond , N. Torkhani , J.R. Partington
关键词: Linear programming 、 Frequency data 、 Approximation theory 、 Pointwise 、 Mathematics 、 Function approximation 、 Noise level 、 Mathematical analysis 、 Noise measurement 、 Bandwidth (signal processing)
摘要: Being given noisy band-limited pointwise measurements of a function f belonging to the disc algebra, we provide computational procedure build an approximation which robustly converges on range frequencies (where measurement points are assumed be dense) as number data tends /spl infin/ and l/sup infin// noise level goes 0, while staying within some Lipschitz-continuous tolerance from behaviour outside bandwidth, being meet this tolerance. >
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