Skip to main content
SpringerLink
Log in

Paraconsistent Neurocomputing and Biological Signals Analysis

  • Chapter
  • First Online:
Book cover Paraconsistent Intelligent-Based Systems

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 94))

Abstract

In this work, we show two applications of Paraconsistent Artificial Neural Network (PANN) for signal analysis working with signal data as a numeric vector and analyzing its morphology, comparing the signal data with a reference database and their application as support for electroencephalogram exams and HIV genotyping.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abe, J.M., Foundations of annotated logics. Ph.D. thesis (in Portuguese) USP, Brazil (1992)

    Google Scholar 

  2. Abe, J.M.: Some aspects of paraconsistent systems and applications. Logique et Anal. 157, 83–96 (1997)

    Google Scholar 

  3. Abe, J.M., Lopes, H.F.S., Anghinah, R.: Paraconsistent artificial neural network and alzheimer disease: a preliminary study. Dement. Neuropsychol. 3, 241–247 (2007)

    Google Scholar 

  4. Anghinah, R.: Estudo da densidade espectral e da coerência do eletrencefalograma em indivíduos adultos normais e com doença de Alzheimer provável. Ph.D. thesis (in Portuguese), FMUSP, São Paulo (2003)

    Google Scholar 

  5. Ansari, D., Karmiloff-Smith, A.: Atypical trajectories of number development: a neuroconstructivist perspective. Trends Cogn. Sci. 12, 511–516 (2002)

    Article  Google Scholar 

  6. Amaral, F.V.: Paraconsistent mammography image attributes classifier in breast cancer diagnosis: based on Paraconsistent Artificial Neural Network. Ph.D. thesis (in Portuguese) UNIP, Brazil (2013)

    Google Scholar 

  7. Barre-Sinoussi, F., et al.: Isolation of a T-lymphotropic retrovirus from a patient at risk for Acquired Immune Deficiency Syndrome (AIDS). Science, vol. 220, pp. 868–871 (1983)

    Google Scholar 

  8. Claus, J.J., Strijers, R.L.M., Jonkman, E.J., Ongerboer De Visser, B.W., Jonker, C., Walstra, G.J.M., Scheltens, P., Gool, W.A.: The diagnostic value of EEG in mild senile Alzheimer´s disease. Clin. Neurophysiol. 18, (15–23) (1999)

    Google Scholar 

  9. Crevel, H., Gool, W.A., Walstra, G.J.M.: Early diagnosis of dementia: which tests are indicated? What are their costs. J. Neurol. 246, 73–78 (1999)

    Article  Google Scholar 

  10. Da Silva Filho, J.I., Abe J.M., Torres, G.L.: Inteligência Artificial com as Redes de Análises Paraconsistentes, (in Portuguese) LTC-Livros Técnicos e Científicos Editora S.A., São Paulo, 313 pág. (2008)

    Google Scholar 

  11. Da Silva Filho, J.I., Torres, G.L., Abe, J.M.: Uncertainty treatment using paraconsistent logic—introducing paraconsistent artificial neural networks, vol. 211. IOS Press, Netherlands, 328 pp. (2010), ISBN 978-1-60750-557-0. doi:10.3233/978-1-60750-558-7-I

  12. Duffy, F.H., Albert, M.S., Mcnulty, G., Garvey, A.J.: Age differences in brain electrical activity of healthy subjects. Ann. Neural. 16, 430–438 (1984)

    Article  Google Scholar 

  13. Grant, A.D., Cock, K.M.D.: ABC of AIDS—HIV infection and AIDS in the developing world. BMJ 322, 1475–1478 (2001)

    Article  Google Scholar 

  14. Gotman, J., Gloor, P., Ray, W.F.: A quantitative comparison of traditional reading of the EEG and interpretation of computer-extracted features in patients with supra tentorial brain lesions. Electroencephalogr. Clin. Neurophysiol. 38, 623–639 (1975)

    Article  Google Scholar 

  15. Gotman, J.: The use of computers in analysis and dysplasia of EEG and evoked potentials. In: Daly, D.D., Pedley, A.T. (eds.) Current Practice of Clinical Electroencephalography, 2nd edn, pp. 51–84. Raven Press, New York (1990)

    Google Scholar 

  16. Kwak, Y.T.: Quantitative EEG findings in different stages of Alzheimer’s disease. J. Clin. Neurophysiol. 23(5), 456–461 (2006)

    Article  Google Scholar 

  17. Klimeshc, W.: EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res. Ver. 29, 169–195 (1999)

    Article  Google Scholar 

  18. Kocyigit, Y., Alkan, A., Erol, H.: Classification of EEG recordings by using fast independent component analysis and artificial neural network. J. Med. Syst. Springer Neth. 32(1), 17–20 (2008)

    Google Scholar 

  19. Lesser, R.P.: Guidelines committees of American electroencephalographic society. J. Clin. Neurophysiol. 11, 09–11 (1994)

    Article  Google Scholar 

  20. Lopes, H.F.S.: Aplicação de redes neurais artificiais paraconsistentes como método de auxílio no diagnóstico da doença de Alzheimer. M.Sc. Dissertation (in Portuguese), Faculdade de Medicina-USP, São Paulo, 473 pp. (2009)

    Google Scholar 

  21. Niedermeyer, E., da Silva, F.L.: Electroencephalography, 5th edn. Lippincott Williams & Wilkins, Philadelphia (2005)

    Google Scholar 

  22. Nuwer, M.R., Comi, G., Emerson, R., Fuglsang-Frederiksen, J., GuériT, M., Hinrichs, H., Ikeda, A., Luccas, F.J.C., Rappelsberger, P.: IFCN standards for digital recording of clinical EEG. Electroencephalogr. Clin. Neurophysiol. 106, 259–261 (1998)

    Article  Google Scholar 

  23. Nitrini, R., Caramelli, P., Bottino, C.M., Damasceno, B.P., Brucki, S.M., Anghinah, R.: Academia Brasileira de Neurologia. Diagnosis of Alzheimer’s disease in Brazil: diagnostic criteria and auxiliary tests. Recommendations of the scientific department of cognitive neurology and aging of the brazilian academy of neurology. Arq Neuropsiquiatr. 63(3A), 713–719 (2005)

    Article  Google Scholar 

  24. Orrison, W.W., Lewine, J.D., Sanders, J.A., Hartshorne, M.F.: Functional brain imaging, pp. 327–368. Mosby, St Louis (1995)

    Google Scholar 

  25. Prusiner, S.R.: Discovering the cause of AIDS. Science 298(5599), 1726–1727 (2002)

    Article  Google Scholar 

  26. Santos, P.C.C.: Banco de Dados Inteligente e Ferramentas Associadas de Seqüências, Mutações e Resistências ao Antiretrovirais do Vírus HIV. Transl. (in Portuguese) Ph.D. thesis, Institute of Biomedical Sciences—USP, São Paulo, Brazil, 183 pp (2010)

    Google Scholar 

  27. Shafer, R.W., Schapiro, J.M.: HIV-1 drug resistance mutations: an update framework for the second decade of HAART. AIDS, vol. 10, pp. 67–84 (rev. 2008)

    Google Scholar 

  28. Shafer, R. W., Dupnik, K., Winters, M.A., Eshlemann, S.H.: HIV-1 reverse transcriptase and protease sequencing for drug resistance studies. In: Kuiken, C., et al. (ed.) HIV Sequence Compendium. Theoretical Biology and Biophysics, Los Alamos, pp. 83–133 (2001)

    Google Scholar 

  29. Souza, S., Abe, J.M., Nakamatsu, K.: MICR automated recognition based on paraconsistent artificial neural networks, vol. 22, pp. 170–178. Procedia Computer Science, Elsevier (2013)

    Google Scholar 

  30. Wong, P.K.H.: Introduction to brain topography, pp. 150–162. Plenum Press, New York (1991)

    Book  Google Scholar 

  31. WIGG, M.D.: Virus da imunodeficiência humana. In: Santos, N.S.O., Romanos, M.T.V., Wigg, M.D. (eds.) Introdução à virologia humana. Guanabara Koogan, Rio de Janeiro, pp. 410–447 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate Program in Production Engineering, ICET—Paulista University, São Paulo, Brazil

    Jair Minoro Abe

  2. Institute for Advanced Studies—University of São Paulo, São Paulo, Brazil

    Jair Minoro Abe

  3. Faculty of Medicine—University of São Paulo, São Paulo, Brazil

    Helder Frederico da Silva Lopes

  4. Reference Center of Behavioral Disturbances and Dementia (CEREDIC) of Faculty of Medicine, University of São Paulo, São Paulo, Brazil

    Renato Anghinah

Authors
  1. Jair Minoro Abe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Helder Frederico da Silva Lopes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Renato Anghinah
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jair Minoro Abe .

Editor information

Editors and Affiliations

  1. São Paulo, Brazil

    Jair Minoro Abe

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Abe, J.M., da Silva Lopes, H.F., Anghinah, R. (2015). Paraconsistent Neurocomputing and Biological Signals Analysis. In: Abe, J. (eds) Paraconsistent Intelligent-Based Systems. Intelligent Systems Reference Library, vol 94. Springer, Cham. https://doi.org/10.1007/978-3-319-19722-7_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-19722-7_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19721-0

  • Online ISBN: 978-3-319-19722-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation