Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Bio-inspired communication: performance limits for information transmission and compression in stochastic pooling networks with binary quantizing nodes

Tools
- Tools
+ Tools

McDonnell, Mark D., Amblard, Pierre-Olivier and Stocks, Nigel G. (2010) Bio-inspired communication: performance limits for information transmission and compression in stochastic pooling networks with binary quantizing nodes. Journal of Computational and Theoretical Nanoscience, Vol.7 (No.5). pp. 876-883. doi:10.1166/jctn.2010.1434

Research output not available from this repository, contact author.
Official URL: http://dx.doi.org/10.1166/jctn.2010.1434

Request Changes to record.

Abstract

A general framework for modeling surprising nonlinear interactions between redundancy and two forms of 'noise'-lossy compression and randomness is discussed. This 'stochastic pooling network' (SPN) model arose from studies of signal transduction by populations of biological sensory neurons, but is also applicable for several modern communications and computing approaches. SPNs are networks that simultaneously exhibit noise-averaging effects caused by redundancy, and lossy signal compression. Here we illustrate some interesting features of a special case of SPN, where individual network nodes are extremely lossy, and transmit single-bit observations of an analog signal. Mutual information is used to quantify the gain obtained from N such observations, which is shown to be limited by quantization noise for large input SNRs, but only by the size of the network for small input SNRs. We show that this means extreme local compression is close to optimal for small SNRs, by a comparison with the mutual information for the case of no compression. Interpretations of these results in terms of rate-distortion theory and probability of error are given indicating that requantization of the output of an SPN can lead to low bit-error-rate communication.

Item Type: Journal Article
Subjects: Q Science > QD Chemistry
T Technology
T Technology > TA Engineering (General). Civil engineering (General)
Q Science > QC Physics
Divisions: Faculty of Science > Engineering
Journal or Publication Title: Journal of Computational and Theoretical Nanoscience
Publisher: American Scientific Publishers
ISSN: 1546-1955
Official Date: May 2010
Dates:
DateEvent
May 2010Published
Volume: Vol.7
Number: No.5
Number of Pages: 8
Page Range: pp. 876-883
DOI: 10.1166/jctn.2010.1434
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: Australian Research Council, Engineering and Physical Sciences Research Council (EPSRC)
Grant number: DP0770747, EP/C523334/1 (EPSRC)

Data sourced from Thomson Reuters' Web of Knowledge

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item
twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us