Image compression and reconstruction using pit-sigma neural networks

Soft Computing

Volumn 11, Issue 1, 2007, Pages 53-61

  Iyoda, Eduardo Masato ^a   Shibata, Takushi ^a   Nobuhara, Hajime ^a   Pedrycz, Witold ^b   Hirota, Kaoru ^a  

^a TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

^b UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Genetic algorithm; High order neural networks; Image compression; Multiplicative neurons; Neural networks

Indexed keywords

EID: 33747617153     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-006-0052-z     Document Type: Article

References (15)

1. Duch W, Jankowski N (1999) Survey of neural transfer functions. Neural Comput Surv 2:163-212
2. Fahlman SE, Lebiere C (1991) The cascade-correlation learning architecture. Technical Report CMU-CS-90-100, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA
3. Ghosh J, Shin Y (1992) Efficient higher-order neural networks for classification and function approximation. Int J Neural Syst 3:323-350
4. Haykin S (1999) Neural networks - a comprehensive foundation 2nd edn. Prentice Hall, Englewood Cliffs
5. t Cascaded hybrid neural network and its application to the spirals and sonar pattern classification problems. In: Proceedings of the 4th international symposium on advanced intelligent systems, Jeju Island, Korea, pp 158-161
6. Iyoda EM, Nobuhara H, Hirota K (2003b) Solving the N -bit parity problem using a single translated multiplicative neuron. Neural Process Lett 18:213-218
7. Iyoda EM, Nobuhara H, Hirota K (2004) Translated multiplicative neuron: an extended multiplicative neuron that can translate decision surfaces. J Adv Comput Intell Intell Inf (to appear)
8. Jiang J (1999) Image compression with neural networks - a survey. Signal Process Imag Commun 14:737-760
9. Leerink LR, Lee Giles C, Horne BG, Jabri MA (1995) Product unit learning. Technical Report CS-TR-3503, University of Maryland, College Park, MD
10. Ma L, Khorasani K (2002) Application of adaptive constructive neural network to image compression. IEEE Trans Neural Netw 13:1112-1126
11. Michalewicz Z (1996) Genetic algorithms + data structures = evolution programs, 3rd edn. Springer, Berlin Heidelberg New York
12. Møller MF (1993) Scaled conjugate gradient algorithm for fast supervised learning. Neural Netw 6:525-533
13. Namphol A, Chin SH, Arozullah M (1996) Image compression with a hierarchical neural network. IEEE Trans Aerosp Electr Sys 32:326-337
14. Schmitt M (2002) On the complexity of computing and learning with multiplicative neurons. Neural Comput 14:241-301
15. Zhang B-T (2002) A bayesian evolutionary approach to the design and learning of heterogeneous neural trees. Integr Comput Aided Eng 9:73-86