To determine the relation of the sparse, distributed memory to other architectures, a broad review of the literature was made. The memory is called a pattern memory because they work with large patterns of features (high-dimensional vectors). A pattern is stored in a pattern memory by distributing it over a large number of storage elements and by superimposing it over other stored patterns. A pattern is retrieved by mathematical or statistical reconstruction from the distributed elements. Three pattern memories are discussed
A new design for a Sparse Distributed Memory, called the selected-coordinate design, is described. A...
A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presente...
The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural netwo...
Described here is sparse distributed memory (SDM) as a neural-net associative memory. It is characte...
Sparse distributed memory was proposed be Pentti Kanerva as a realizable architecture that could sto...
The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massivel...
Pentti Kanerva is working on a new class of computers, which are called pattern computers. Pattern c...
When a set of patterns is stored in a distributed memory, any given storage location participates in...
Previously, a method was described of representing a class of simple visual images so that they coul...
If the stored input patterns of Kanerva's Sparse Distributed Memory (SDM) are highly correlated, uti...
Abstract—The Sparse Distributed Memory (SDM) proposed by Kanerva provides a simple model for human l...
Challenging AI applications, such as cognitive architectures, natural language understanding, and vi...
For a number of years, artificial neural networks have been used for a variety of applications to au...
The Sparse Distributed Memory (SDM)[1] was originally developed to tackle the problem of storing lar...
The standard formulation of Kanerva's sparse distributed memory (SDM) involves the selection of a la...
A new design for a Sparse Distributed Memory, called the selected-coordinate design, is described. A...
A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presente...
The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural netwo...
Described here is sparse distributed memory (SDM) as a neural-net associative memory. It is characte...
Sparse distributed memory was proposed be Pentti Kanerva as a realizable architecture that could sto...
The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massivel...
Pentti Kanerva is working on a new class of computers, which are called pattern computers. Pattern c...
When a set of patterns is stored in a distributed memory, any given storage location participates in...
Previously, a method was described of representing a class of simple visual images so that they coul...
If the stored input patterns of Kanerva's Sparse Distributed Memory (SDM) are highly correlated, uti...
Abstract—The Sparse Distributed Memory (SDM) proposed by Kanerva provides a simple model for human l...
Challenging AI applications, such as cognitive architectures, natural language understanding, and vi...
For a number of years, artificial neural networks have been used for a variety of applications to au...
The Sparse Distributed Memory (SDM)[1] was originally developed to tackle the problem of storing lar...
The standard formulation of Kanerva's sparse distributed memory (SDM) involves the selection of a la...
A new design for a Sparse Distributed Memory, called the selected-coordinate design, is described. A...
A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presente...
The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural netwo...