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- Christopher J. Rozell, Don H. Johnson, Richard G. Baraniuk, Bruno A. Olshausen
- Neural Computation
- 2008

While evidence indicates that neural systems may be employing sparse approximations to represent sensed stimuli, the mechanisms underlying this ability are not understood. We describe a locally competitive algorithm (LCA) that solves a collection of sparse coding principles minimizing a weighted combination of mean-squared error and a coefficient cost… (More)

- Don H. Johnson
- Journal of Computational Neuroscience
- 1996

In most neural systems, neurons communicate via sequences of action potentials. Contemporary models assume that the action potentials' times of occurrence rather than their waveforms convey information. The mathematical tool for describing sequences of events occurring in time and/or space is the theory of point processes. Using this theory, we show that… (More)

We define a new distance measure the resistor-average distance between two probability distributions that is closely related to the Kullback-Leibler distance. While the KullbackLeibler distance is asymmetric in the two distributions, the resistor-average distance is not. It arises from geometric considerations similar to those used to derive the Chernoff… (More)

THE fast Fourier transform (Fm has become well known . as a very efficient algorithm for calculating the discrete Fourier Transform (Om of a sequence of N numbers. The OFT is used in many disciplines to obtain the spectrum or . frequency content of a Signal, and to facilitate the computation of discrete convolution and correlation. Indeed, published work on… (More)

- Don H. Johnson, Charlotte M. Gruner
- Journal of Computational Neuroscience
- 1998

We describe an approach to analyzing single- and multiunit (ensemble) discharge patterns based on information-theoretic distance measures and on empirical theories derived from work in universal signal processing. In this approach, we quantify the difference between response patterns, whether time-varying or not, using information-theoretic distance… (More)

- Wei Wang, Don H. Johnson
- IEEE Trans. Signal Processing
- 2002

Signals that represent information may be classified into two forms: numeric and symbolic. Symbolic signals are discrete-time sequences that at, any particular index, have a value that is a member of a finite set of symbols. Set membership defines the only mathematical structure that symbolic sequences satisfy. Consequently, symbolic signals cannot be… (More)

- C. C. Leang, Don H. Johnson
- IEEE Trans. Information Theory
- 1997

is a minimum phase channel since {h , } i s maximum phase [7] . Many system implementations that transmit data in frames or blocks already have buffers built into the system, and thus already have a delay equal to this frame length. The decoding delay of the backward decoder is this length plus whatever time is needed to complete the decoder calculations.… (More)

- Don H. Johnson, C. Richard Johnson, Robert G. Erdmann
- Signal Processing
- 2013

A spectral algorithm is described for measuring from radiographs the weaving densities of the horizontal and vertical threads that comprise a painting’s canvas. A framework for relating spectra to canvas weave type is presented. The so-called thread density and angle maps obtained from the algorithm reveal the canvas’s distinctive density variations and… (More)

- Kathryn S. McKinley, Ken Kennedy, +5 authors Don H. Johnson
- 1994

The goal of this dissertation is to give programmers the ability to achieve high performance by focusing on developing parallel algorithms, rather than on architecture-speciic details. The advantages of this approach also include program portability and legibility. To achieve high performance, we provide automatic compilation techniques that tailor parallel… (More)

- Don H. Johnson, Geoffrey C. Orsak
- IEEE Trans. Communications
- 1993