Abstract
Level crossing based sampling might be used as an alternative to Nyquist theory based sampling of a signal. Level crossing based approach take advantage of statistical properties of the signal, providing cues to efficient nonuniform sampling. This paper presents new threshold level allocation schemes for level crossing based nonuniform sampling. Intuitively, it is more reasonable if the information rich regions of the signal are sampled finer and those with sparse information are sampled coarser. To achieve this objective, we proposed non-linear quantization functions which dynamically assign the number of quantization levels depending on the importance of the given amplitude range. Various aspects of proposed techniques are discussed and experimentally validated. Its efficacy is investigated by comparison with Nyquist based sampling.
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Nagesha, Kumar, G.H. (2007). Signal Resampling Technique Combining Level Crossing and Auditory Features. In: Ghosh, A., De, R.K., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2007. Lecture Notes in Computer Science, vol 4815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77046-6_55
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DOI: https://doi.org/10.1007/978-3-540-77046-6_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77045-9
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