Sparse Learning of Higher-Order Statistics for Communications and Sensing
Sparse Learning of Higher-Order Statistics for Communications and Sensing is a scholarly work, published in 2020 in ''IEEE Transactions on Emerging Topics in Computational Intelligence''. The main subjects of the publication include independent component analysis, Higher-order statistics, stock order, Speech enhancement, compressed sensing, statistics, order statistic, and computer science. The authors formulate the issue of sparse representation of HOS by categorizing them into three cases according to the discriminative sparsity: strictly sparse, structure-based sparse and structure-based compressible.