Neural Processing Letters

, Volume 2, Issue 2, pp 27–30 | Cite as

Improving the Counterpropagation network performances

  • Alessandra Chiuderi


This paper deals with the problem of how input data normalization can affect the performances of the Counterpropagtion neural network. In the following, an example drawn from the landcover classification of remotely sensed images is presented and a solution, based on the Decorrelation Stretching technique, is proposed.


Neural Network Artificial Intelligence Input Data Complex System Nonlinear Dynamics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [1]
    R.H. Nielsen. Counterpropagation networks,Applied Optics, vol. 26, no. 23, pp. 4979–4984, 1987.ADSGoogle Scholar
  2. [2]
    P.D. Wasserman.Neural Computing, Theory and Practice, Van Nostrand Reinhold, New York, 1989.Google Scholar
  3. [3]
    A.R. Gillespie, A.B. Kahle, R.E. Walker. Color enhancement of highly correlated images — I — Decorrelation stretching and HSI contrast stretches.Remote Sensing of Environment, vol. 20, pp. 209–235, 1986.CrossRefGoogle Scholar
  4. [4]
    C. Bechini, L. Chiarantini, P. Ciotti, S. Moretti, E Pettinelli, N. Pierdicca. MAC'19 on Montespertoli: preliminary assessment of land polarimetric features,Proc. IGARSS, vol. 1, pp. 395–397, 1992.Google Scholar
  5. [5]
    P. Coppo, P. Ferrazzoli, G. Luzi, S. Paloscia, G. Schiavon, C. Susini. MAC'91 on Montespertoli: preliminary analysis of multifrequency SAR sensitivity to soli and vegetation paramenters,Proc. IGARSS, Vol. 1, pp. 489–491, 1992.Google Scholar
  6. [6]
    G. G. Wilkinson. The processing and interpretation of remotely-sensed satellite imagery: a current view,Remote Sensing and Geographial Information Systems for Resource Management in Developing Countries, pp. 71–96, 1991.Google Scholar

Copyright information

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • Alessandra Chiuderi
    • 1
  1. 1.Electronic Engineering DepartmentUniversity of FlorenceFirenzeItaly

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