Advertisement

Hybrid Validation of Handwriting Process Modelling

  • Mohamed Aymen Slim
  • Maroua El Kastouri
  • Afef Abdelkrim
  • Mohamed Benrejeb
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7664)

Abstract

Handwriting process is one of the most complex processes of our biological repertory. Modelling such process remains difficult to implement. Several approaches were proposed in the literature. However, the validation results of these models remain less or more satisfactory. This paper deals with unconventional and conventional handwriting process characterization approaches based on the use of soft computing techniques namely the Radial Basis Function (RBF) neural networks and the use of mathematical models based on the recursive least squares algorithm. Modelling handwriting system as well as the hybrid validation of the proposed models constitutes the main contribution of this paper. The obtained simulation results of the hybrid validation models show a satisfactory agreement between responses of the developed models and the experimental Electromyographic signals (EMG) data then the efficiency of the proposed approaches. Applying the study is very interesting to elaborate a helpful system to those who suffer from physical handicaps.

Keywords

Handwriting Process Experimental Approach Modelling Electromyographic Signals RBF Neural Networks Hybrid Validation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Van Der Gon, D., Thuring, J.P., Strackee, J.: A Handwriting Simulator. Phys. Med. Biol. 407–414 (1962)Google Scholar
  2. 2.
    MacDonald, J.S.: Experimental Studies of Handwriting Signals. Ph. D. Dissertation, Mass. Inst. Tech., Cambridge (1964)Google Scholar
  3. 3.
    Yasuhara, M.: Experimental Studies of Handwriting Process. Rep. Univ. Electro-Comm. Japan 25-2, 233–254 (1975)Google Scholar
  4. 4.
    Edelman, S., Flash, T.: A Model of Handwriting. Biol. Cybern. 57, 25–36 (1987)CrossRefGoogle Scholar
  5. 5.
    Sano, M., Kosaku, T., Murata, Y.: Modeling of Human Handwriting Motion by Electromyographic Signals on Foream Muscles. In: CCCT 2003, Orlando-Florida (2003)Google Scholar
  6. 6.
    Benrejeb, M., El Abed-Abdelkrim, A., Sano, M.: Sur l’étude du Processus d’écriture à la main. Approches Classiques et non Conventionnelles. Revue e-STA 3, Premier trimestre (2006) (in French)Google Scholar
  7. 7.
    Abdelkrim, A.: Contribution à la modélisation du processus d’écriture à la main par approches relevant du calcul évolutif. Thèse de Doctorat, ENIT. Tunis (2005) (in French)Google Scholar
  8. 8.
    Abdelkrim, A., Benrejeb, M., Sano, M.: PAW Handwriting Neural System. In: IEEE International Conference on Communication, Computer and Power, ICCCP 2001, Muscat, pp. 207–211 (2001)Google Scholar
  9. 9.
    De Coulon, F.: Théorie et Traitement des Signaux, vol. 6. Presses Polytechniques Romandes, Lausane (1984) (in French)Google Scholar
  10. 10.
    Slim, M.A., Abdelkrim, A., Benrejeb, M.: RBF Neural Networks for Handwriting Process Modeling. In: Third IEEE International Conference on Soft Computing and Pattern Recognition, SoCPaR 2011, Dalian China, pp. 384–389 (2011)Google Scholar
  11. 11.
    Yang, Z.R.: A Novel Radial Basis Function Neural Network for Discriminant Analysis. IEEE Trans. Neural Networks 17, 604–612 (2006)CrossRefGoogle Scholar
  12. 12.
    Borne, P., Benrejeb, M., Haggège, J.: Les réseaux de Neurones. Présentation et Application. Ed. Technip, Paris (2007) (in French)Google Scholar
  13. 13.
    Moody, J., Antsaklis, P.J.: The Dependence Identification Neural Network Construction Algorithm. IEEE Trans. Neural Networks 7, 3–15 (1996)CrossRefGoogle Scholar
  14. 14.
    Sifaoui, A., Abdelkrim, A., Alouane, S., Benrejeb, M.: On New RBF Neural Network Construction Algorithm for Classification. Studies Inform. Control 18, 103–110 (2009)Google Scholar
  15. 15.
    Landau, I.D.: Identification et Commande des Systèmes. Ed. Hermès, Paris (1993) (in French)Google Scholar
  16. 16.
    Chihi, I., Ghorbel, C., Abdelkrim, A., Benrejeb, M.: Parametric Identification of Handwriting System Based on RLS Algorithm. In: International Conference on Control, Automation and Systems, ICCAS 2011, Kintex Gveonggi-do Korea (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mohamed Aymen Slim
    • 1
  • Maroua El Kastouri
    • 1
  • Afef Abdelkrim
    • 1
  • Mohamed Benrejeb
    • 1
  1. 1.LA.R.A LaboratoryNational Engineering School of TunisTunisTunisia

Personalised recommendations