Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Generalized Unary Coding

  • Short Paper
  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

Unary coding is useful, but it is redundant in its standard form. It can be seen as spatial coding where the value of the number is determined by its place in an array as is true in the generation of neural sequences in songbirds. Motivated by the biological finding that several neurons in the vicinity represent the same number, we propose a variant of unary numeration in its spatial form, where each number is represented by several 1s. We call this spread unary coding where the number of 1s used is the spread of the code. Spread unary coding is associated with saturation of the Hamming distance between code words. Extended variants of spread unary coding are described. These schemes, in which the length of the code word is fixed, allow representation of approximately \(n^{2}\) numbers for n bits, rather than the n numbers of the standard unary coding. In the first scheme the spread increases, whereas in the second scheme the spread remains constant.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. I.R. Fiete, R.H. Hahnloser, M.S. Fee, H.S. Seung, Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong. J. Neurophysiol. 92(4), 2274–2282 (2004)

    Article  Google Scholar 

  2. I.R. Fiete, W. Senn, C.Z.H. Wang, R.H.R. Hahnloser, Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity. Neuron 65, 563–576 (2010)

    Article  Google Scholar 

  3. I.R. Fiete, H.S. Seung, Neural network models of birdsong production, learning, and coding, in New Encyclopedia of Neuroscience, ed. by L. Squire, T. Albright, F. Bloom, F. Gage, N. Spitzerin (Elsevier, Amsterdam, 2007)

    Google Scholar 

  4. S.W. Golomb, Run-length encodings. IEEE Trans. Inf. Theory IT–12, 399–401 (1996)

    MATH  Google Scholar 

  5. R.H.R. Hahnloser et al., An ultra-sparse code underlies the generation of neural sequences in a songbird. Nature 419, 65–70 (2002)

    Article  Google Scholar 

  6. S. Kak, On generalization by neural networks. Inf. Sci. 111, 293–302 (1998)

    Article  Google Scholar 

  7. S. Kak, Faster web search and prediction using instantaneously trained neural networks. IEEE Intell. Syst. 14, 79–82 (1999)

    MathSciNet  Google Scholar 

  8. S. Kak, A class of instantaneously trained neural networks. Inf. Sci. 148, 97–102 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  9. J.M. Moore et al., Motor pathway convergence predicts syllable repertoire size in oscine birds. Proc. Nat. Acad. Sci. USA 108, 16440–16445 (2011)

    Article  Google Scholar 

  10. F. Nottebhom, Brain pathway for vocal learning in birds: a review of the first 10 years. Prog. Psychobiol. Physiol. Psychol. 9, 85–124 (1980)

    Google Scholar 

  11. J.F. Prather, S. Peters, S. Nowicki, R. Mooney, Precise auditory-vocal mirroring in neurons for learned vocal communication. Nature 451, 305–310 (2008)

    Article  Google Scholar 

  12. R.F. Rice, R. Plaunt, Adaptive variable-length coding for efficient compression of spacecraft television data. IEEE Trans. Commun. 16, 889–897 (1971)

    Article  Google Scholar 

  13. K.-W. Tang, S. Kak, A new corner classification approach to neural network training. Circuits Syst. Signal Process. 17, 459–469 (1998)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Subhash Kak.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kak, S. Generalized Unary Coding. Circuits Syst Signal Process 35, 1419–1426 (2016). https://doi.org/10.1007/s00034-015-0120-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-015-0120-7

Keywords

Navigation