Storing and retrieving data in a parallel distributed-memory system. Doctoral thesis
The storage and retrieval of patterns in a Hopfield-like Parallel Distributed Memory is investigated experimentally with a view toward increasing its storage capacity. The first two chapters gives an overview of distributed memories and, in particular, the Hopfield distributed memory. This is followed by a chapter which experimentally identifies the basic storage capacity of the original Hopfield memory when using text patterns. This discussion then experimentally investigates new and untested methods to increase the storage capabilities of a Hopfield-like neural net. Increasing the storage capacity by using the continuous-valved Hopfield memory is explored in chapter 3 and the impact on capacity of data representation is experimentally investigated in chapter 4. We then focus on new ways of storing data (changing the interconnect strengths) including in Chapter 7 developing a new method called Modifying the Energy Contour or MEC. In addition, this Chapter also outlines how to increase error-tolerance through the use of noisy patterns.
- Research Organization:
- Brown Univ., Providence, RI (USA). Center for Neural Science
- OSTI ID:
- 7077296
- Report Number(s):
- AD-A-195631/7/XAB; TR-45
- Country of Publication:
- United States
- Language:
- English
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