In this article, we analyze the use of the continuous classifying associative memory (CCLAM) to store linguistic information. Freedom in the choice of the functions that control the operation of the CCLAM equip this memory with the capacity to adapt to different information storage and recovery needs. We begin with the problem of storing linguistic terms by memorizing the patterns formed by the...

The Hopfield network (Hopfield, 1982,1984) provides a simple model of an associative memory in a neuronal structure. This model, however, is based on highly artificial assumptions, especially the use of formal-two state neu-rons (Hopfield, 1982) or graded-response neurons (Hopfield, 1984). \Vhat happens if we replace the formal neurons by 'real' biological neurons? \Ve address this question in ...

Most models of neural associative memory have used networks with broad connectivity. However, from both a neurobiological viewpoint and an implementation perspective, it is logical to minimize the length of inter-neural connections and consider networks whose connectivity is predominantly local. The \small-world networks" model described recently by Watts and Strogatz provides an interesting ap...

Fast content addressable data access mechanisms have compelling applications in today’s systems. Many of these exploit the powerful wildcard matching capabilities provided by ternary content addressable memories. For example, TCAM based implementations of important algorithms in data mining been developed in recent years; these achieve an an order of magnitude speedup over prevalent techniques....

Associative memory, as a form of computing-with-memory, reduces energy of the processing elements by eliminating redundant computations [2], [8], [11]–[15], [17]–[20]. An associative memory can quickly recall responses of a function for a subset of input patterns to save energy by avoiding the actual function execution on the processing element. An associative memory is typically composed of a ...

We consider Whittle's probabilistic content addressable memory, the antiphon, which is designed for recovering stored patterns from nonlinear distortions of the input messages. We give an application to content-based image retrieval systems and propose canonical ways of choosing similarity thresholds ensuring statistical consistency.

Leveraging nanotechnology for computing opens up exciting new avenues for breakthroughs. For example, graphene is an emerging nanoscale material and is believed to be a potential candidate for post-Si nanoelectronics due to high carrier mobility and extreme scalability. Recently, a new graphene nanoribbon crossbar (xGNR) device was proposed which exhibits negative differential resistance (NDR)....