Narrow Results

A dynamic memory is a storage medium constituted by an array of cells and an interconnection network between them. It is characterized by the constant circulation of the stored data. The objective is to design the interconnection network in order to have small access times and a simple memory control. Several interconnection schemes have been proposed in the literature. This paper presents a quite general model for such structures that greatly facilitates both the design and the control of the memory. Most previous proposals of dynamic memory interconnection networks are particular instances of our model. Moreover, our approach is used to obtain new proposals of interconnection topologies for dynamic memories and fast cyclic shift registers. Namely, a model that optimizes both the access time and the size of the memory and two memory organizations for sequential access are presented.

In this paper, we propose a Star cellular neural network (Star CNN) for associative and dynamic memories. A Star CNN consists of local oscillators and a central system. All oscillators are connected to a central system in the shape of a Star, and communicate with each other through a central system. A Star CNN can store and retrieve given patterns in the form of synchronized chaotic states with appropriate phase relations between the oscillators (associative memories). Furthermore, the output pattern can occasionally travel around the stored patterns, their reverse patterns, and new relevant patterns which are called spurious patterns (dynamic memories).