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Experiments with Neural Network Libraries

Khazanova, Yekaterina
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1527607591612278

Abstract Details

2013, MS, University of Cincinnati, Engineering and Applied Science: Computer Science.
When solving problems using neural networks, the user/developer is usually limited by the number of neural networks he or she has already studied or descriptions of which are readily available. If there was a library of many neural networks, one easy to access and intuitive to use, it would greatly assist developers in nding the optimum method for their needs, as well determining on average which neural networks are better suited to which problems. This project was part of a larger work to compile a library of neural networks. During the course of the research we explored the Zak Model, the Torus Attractor Model, the Hopeld Model, and the Kaneko Model - their usefulness in solving pattern recognition problems and their stability.
Anca Ralescu, Ph.D. (Committee Chair)
Elena N. Benderskaya, Ph.D. (Committee Member)
Chia Han, Ph.D. (Committee Member)
89 p.
Artificial Intelligence

Recommended Citations

Citations

  • Khazanova, Y. (2013). Experiments with Neural Network Libraries [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1527607591612278

    APA Style (7th edition)

  • Khazanova, Yekaterina. Experiments with Neural Network Libraries. 2013. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1527607591612278.

    MLA Style (8th edition)

  • Khazanova, Yekaterina. "Experiments with Neural Network Libraries." Master's thesis, University of Cincinnati, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1527607591612278

    Chicago Manual of Style (17th edition)

ucin1527607591612278
168
© 2013, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.