Now showing items 1-5 of 5
Diverging moments and parameter estimation
Heavy tailed distributions enjoy increased popularity and become more readily applicable as the arsenal of analytical and numerical tools grows. They play key roles in modeling approaches in networking, finance, hydrology ...
A Multiscale Data Representation for Distributed Sensor Networks: Proofs of Basis Characteristics and Error Bounds
Provides proofs of Parseval tight-frame membership and approximation properties for the basis proposed in "A Multiscale Data Representation for Distributed Sensor Networks" by R. Wagner, S. Sarvotham, and R. Baraniuk (ICASSP ...
Multiscale Likelihood Analysis and Complexity Penalized Estimation
We describe here a framework for a certain class of multiscale likelihood factorization wherein, in analogy to a wavlet decomposition of an LÂ² function, a given likelihood function has an alternative representation as a ...
ForWaRD: Fourier-Wavelet Regularized Deconvolution for Ill-Conditioned Systems
We propose an efficient, hybrid <i>Fourier-Wavelet Regularized Deconvolution</i> (ForWaRD) algorithm that performs noise regularization via scalar shrinkage in both the Fourier and wavelet domains. The Fourier shrinkage ...
Directional Hypercomplex Wavelets for Multidimensional Signal Analysis and Processing
We extend the wavelet transform to handle multidimensional signals that are smooth save for singularities along lower-dimensional manifolds. We first generalize the complex wavelet transform to higher dimensions using a ...