Restricted Isometry Property of Gaussian Random Projection for Finite Set of Subspaces
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2017.2778685
Abstract: Dimension reduction plays an essential role when decreasing the complexity of solving large-scale problems. The well-known Johnson–Lindenstrauss (JL) lemma and restricted isometry property (RIP) admit the use of random projection to reduce the dimension while… read more here.
Keywords: restricted isometry; random projection; isometry property; gaussian random ... See more keywords
Unraveling the Veil of Subspace RIP Through Near-Isometry on Subspaces
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2020.2984905
Abstract: Dimensionality reduction is a popular approach to tackle high-dimensional data with low-dimensional nature. Subspace Restricted Isometry Property, a newly-proposed concept, has proved to be a useful tool in analyzing the effect of dimensionality reduction algorithms… read more here.
Keywords: isometry property; subspace restricted; near isometry; restricted isometry ... See more keywords
Sparse distributed sensor placement via statistical restricted isometry property
Sign Up to like & getrecommendations! Published in 2017 at "Journal of the Acoustical Society of America"
DOI: 10.1121/1.4988559
Abstract: Perfect sensor coverage of large ocean volumes is an intractable problem for small N systems. Instead, this paper presents optimal placement of relatively few sensors in order to achieve coherent array processing. The sensor placement… read more here.
Keywords: restricted isometry; statistical restricted; sensor placement; placement ... See more keywords