The Wavelet Transform

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Gabor Frames and Totally Positive Functions (2011, background): “Much effort has been spent to improve the analytic estimates and make this neighborhood as large as possible [5,9,26].”
A basis for efficient representation of the S-transform (2007, background): “The DWT using Daubechies wavelets is a powerful tool useful in many applications (e.g., image compression, etc.), however, a clearer time-frequency representation is desired.”
Enhanced random search based incremental extreme learning machine (2008, background): “The hidden nodes of SLFNs can be neuron alike or non-neuron alike, including additive or radial basis function (RBF) type of nodes [8], multiplicative nodes, fuzzy rules [10], fully complex nodes [15,19], hinging functions [2], high-order nodes [5], ridge polynomials [22], wavelets [3,4], Fourier te”