Now showing items 81-85 of 85
Wavelet-Based Transformations for Nonlinear Signal Processing
Nonlinearities are often encountered in the analysis and processing of real-world signals. This paper develops new transformations for nonlinear signal processing. The theory of tensor norms is employed to show that wavelets ...
Hybrid Linear/Quadratic Time-Frequency Attributes
We present an efficient method for robustly calculating time-frequency attributes of a signal, including instantaneous mean frequency, bandwidth, and kurtosis. Most current approaches involve a costly intermediate step of ...
Robust Distributed Estimation Using the Embedded Subgraphs Algorithm
We propose a new iterative, distributed approach for linear minimum mean-square-error (LMMSE) estimation in graphical models with cycles. The embedded subgraphs algorithm (ESA) decomposes a loopy graphical model into a ...
Variable-Rate Universal Slepian-Wolf Coding with Feedback
Traditional Slepian-Wolf coding assumes known statistics and relies on asymptotically long sequences. However, in practice the statistics are unknown, and the input sequences are of finite length. In this finite regime, ...
Hybrid Linear/Bilinear Time-Scale Analysis
We introduce a new method for the time-scale analysis of nonstationary signals. Our work leverages the success of the â time-frequency distribution series/cross-term deleted representationsâ into the time-scale domain ...