Now showing items 61-70 of 85
Unitary Equivalence and Signal Processing
The notions of time, frequency, and scale are generalized using concepts from unitary operator theory and eigenanalysis. The result is an infinite number of new signal analysis and processing tools that are implemented ...
Additive and Multiplicative Mixture Trees for Network Traffic Modeling
Network traffic exhibits drastically different statistics, ranging from nearly Gaussian marginals and long range dependence at very large time scales to highly non-Gaussian marginals and multifractal scaling on small scales. ...
Wavelet Statistical Models and Besov Spaces
Hidden Markov Models for Wavelet-based Signal Processing
Current wavelet-based statistical signal and image processing techniques such as shrinkage and filtering treat the wavelet coefficients as though they were statistically independent. This assumption is unrealistic; considering ...
Connection-level Analysis and Modeling of Network Traffic
Most network traffic analysis and modeling studies lump all connections together into a single flow. Such aggregate traffic typically exhibits long-range-dependent (LRD) correlations and non-Gaussian marginal distributions. ...
Distributed Compressed Sensing of Jointly Sparse Signals
Compressed sensing is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for reconstruction. In this paper we expand our theory for ...
Shift-Invariant Denoising using Wavelet-Domain Hidden Markov Trees
Wavelet-domain hidden Markov models have proven to be useful tools for statistical signal and image processing. The hidden Markov tree (HMT) model captures the key features of the joint statistics of the wavelet coefficients ...
Asymptotic Performance of Transmit Diversity via OFDM for Multipath Channels
Many wireless systems exploit transmit diversity for more reliable detection of signals at the receiver. To accomplish this, coding is spread across multiple transmit antennas. An example of this is the well known "Alamouti ...
Contraction, Smoothness, and Low-Pass Filtering
We introduce a generalized definition for "low-pass" filters that covers time-varying and nonlinear systems under the same umbrella. We show that the qualitative concept of signal smoothing can be made precise through the ...
Nonlinear Wavelet Transforms for Image Coding via Lifting
We investigate central issues such as invertibility, stability, synchronization, and frequency characteristics for nonlinear wavelet transforms built using the lifting framework. The nonlinearity comes from adaptively ...