OSA's Digital Library

Applied Optics

Applied Optics


  • Vol. 27, Iss. 3 — Feb. 1, 1988
  • pp: 534–540

Directed graph for adaptive organization and learning of a knowledge base

David Casasent and Edward Baranoski  »View Author Affiliations

Applied Optics, Vol. 27, Issue 3, pp. 534-540 (1988)

View Full Text Article

Enhanced HTML    Acrobat PDF (937 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



A directed graph is considered for organization of a knowledge base for neural, associative, model-based, and other advanced processors. Its ability to self-organize itself, delete old information, and add new information and its many interconnections make it most suitable for optical realization and use in advanced neural and adaptive optical processors. An alphanumeric image space example is used as a case study, and an optical processor architecture to achieve this with impressive performance is discussed.

© 1988 Optical Society of America

Original Manuscript: September 25, 1987
Published: February 1, 1988

David Casasent and Edward Baranoski, "Directed graph for adaptive organization and learning of a knowledge base," Appl. Opt. 27, 534-540 (1988)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. Technical Digest, Topical Meeting on Optical Computing (Optical Society of America, Washington, DC, 1985).
  2. Technical Digest, Topical Meeting on Optical Computing (Optical Society of America, Washington, DC, 1987).
  3. N. Christofides, Graph Theory: An Algorithmic Approach (Academic, New York, 1975).
  4. E. Baranoski, D. Casasent, “A Directed Graph Optical Processor,” Proc. Soc. Photo-Opt. Instrum. Eng. 752, 58 (1987).
  5. P. H. Swain, H. Hauska, “The Decision Tree Classifier: Design and Potential,” IEEE Trans. Geosci. Electron. GE-15, 142 (1977).
  6. E. M. Rounds, “A Combined Nonparametric Approach to Feature Selection and Binary Decision Tree Design,” Pattern Recognition 12, 313 (1980). [CrossRef]
  7. I. K. Sethi, G. P. R. Sarvarayudo, “Hierarchical Classifier Design Using Mutual Information,” IEEE Trans. Pattern Anal. Machine Intell. PAMI-4, 441 (1982). [CrossRef]
  8. D. A. Jared, D. J. Ennis, “Learned Pattern Recognition Using Synthetic-Discriminant-Functions,” Proc. Soc. Photo-Opt. Instrum. Eng. 638, 91 (1986).
  9. H. S. Stone, P. Sipala, “The Average Complexity of Depth-First Search with Backtracking and Cutoff,” IBM J. Res. Dev. 30, 242 (1986). [CrossRef]
  10. S. Kirkpatrick, C. D. Gelatt, M. P. Vecchi, “Optimization by Simulated Annealing,” Science 220, 671 (1983). [CrossRef] [PubMed]
  11. J. M. Wozencraft, I. M. Jacobs, Principles of Communication Engineering (Wiley, New York, 1965).
  12. Special Issue on Optical Computing, Proc. IEEE 72 (July1984).
  13. J. W. Goodman, F. J. Leonberger, S-Y. Kung, R. A. Athale, “Optical Interconnections for VLSI Systems,” Proc., IEEE 72, 850 (1984). [CrossRef]
  14. Special Issue on Optical Interconnections, Opt. Eng. 25, No. 10 (Oct.1986).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited