Now showing items 1-10 of 242
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 ...
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 ...
Distributed Wavelet Transform for Irregular Sensor Network Grids
Wavelet-based distributed data processing holds much promise for sensor networks; however, irregular sensor node placement precludes the direct application of standard wavelet techniques. In this paper, we develop a new ...
Distributed Multiscale Data Analysis and Processing for Sensor Networks
While multiresolution data analysis, processing, and compression hold considerable promise for sensor network applications, progress has been confounded by two factors. First, typical sensor data are irregularly spaced, ...
Geometric Methods for Wavelet-Based Image Compression
Natural images can be viewed as combinations of smooth regions, textures, and geometry. Wavelet-based image coders, such as the space-frequency quantization (SFQ) algorithm, provide reasonably efficient representations for ...
Random Projections of Smooth Manifolds
Many types of data and information can be described by concise models that suggest each data vector (or signal) actually has â few degrees of freedomâ relative to its size N. This is the motivation for a variety of ...