Chinh Dang
ABSTRACT
In this paper, we describe a novel manifold-based interpolation method for sensed environmental data. Furthermore, we present initial results for applying the proposed method to estimate wind speed and direction around Lake Michigan. The proposed method is showing promising results based on the hypothesis that an environmental dataset (including longitude, latitude time, and measured parameters) can be mapped onto an underlying differential manifold. Our preliminary results show that the proposed manifold-based approach outperforms state-of-the-art interpolation and estimation methods.
- Chinh Dang, et al. "Image Super-resolution via Local Self-learning Manifold Approximation"- IEEE Signal Processing Letters, Vol. 21, No. 10, October 2014.Google Scholar
Cross Ref
- Chinh Dang, et al. "Single Image Super Resolution via Manifold Linear Approximation using Sparse Subspace Clustering." In IEEE Global Conference on Signal and Information Processing, pp. 949--953. 2013.Google ScholarCross Ref
- Nguyen, Tuan D., et al. "Summer circulation and exchange in the Saginaw BayLake Huron system." Journal of Geophysical Research: Oceans 119.4 (2014): 2713--2734.Google ScholarCross Ref
- Tenenbaum, Joshua B., et al. "A global geometric framework for nonlinear dimensionality reduction." Science 290, no. 5500 (2000): 2319--2323.Google ScholarCross Ref
Index Terms
- Wind speed and direction estimation using manifold approximation
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