Now showing items 1-10 of 508
Sparse Coding with Population Sketches
(BMC Neuroscience, 2009-07-13)
Neural population structures and consequences for neural coding
Researchers studying neural coding have speculated that populations of neurons would more effectively represent the stimulus if the neurons "cooperated:" by interacting through lateral connections, the neurons would process ...
New Dimensions In Wavelet Analysis
In this paper we propose a new class of signal analysis tools that generalizes the popular wavelet and short-time Fourier transforms. The class allows skews and rotations of the analyzing wavelet in the time-frequency ...
Wavelet-Based Deconvolution Using Optimally Regularized Inversion for Ill-Conditioned Systems
We propose a hybrid approach to wavelet-based deconvolution that comprises Fourier-domain system inversion followed by wavelet-domain noise suppression. In contrast to conventional wavelet-based deconvolution approaches, ...
Nonlinear Wavelet Transforms for Image Coding
We examine the central issues of invertibility, stability, artifacts, and frequency-domain characteristics in the construction of nonlinear analogs of the wavelet transform. The lifting framework for wavelet construction ...
Sharing Knowledge and Building Communities in Signal Processing
The textbook has traditionally been the fundamental tool of university teaching. The text both serves as the repository of facts and information and provides the recommended structure and sequence for teaching and learning ...
Wavelet-Based Denoising Using Hidden Markov Models
Hidden Markov models have been used in a wide variety of wavelet-based statistical signal processing applications. Typically, Gaussian mixture distributions are used to model the wavelet coefficients and the correlation ...
A new look at the informational gain of soft decisions
This paper develops a new systematic method of studying the benefits of 2-bit soft decisions by applying the concepts of information processing theory. We quantify performance in terms of the information transfer ratio and ...
Measurements vs. Bits: Compressed Sensing meets Information Theory
Compressed sensing is a new framework for acquiring sparse signals based on the revelation that a small number of linear projections (measurements) of the signal contain enough information for its reconstruction. The ...
Time-Frequency Based Distance and Divergence Measures
A study of the phase and amplitude sensitivity of the recently proposed Renyi time-frequency information measure leads to the introduction of a new "Jensen-like" divergence measure. While this quantity promises to be a ...