Extended Sparse Distributed Memory

نویسندگان

  • Javier Snaider
  • Stan Franklin
چکیده

Sparse distributed memory is an auto-associative memory system that stores high dimensional Boolean vectors. Here we present an extension of the original SDM that uses word vectors of larger size than address vectors. This extension preserves many of the desirable properties of the original SDM: autoassociability, content addressability, distributed storage, robustness over noisy inputs. In addition, it adds new functionality, enabling an efficient auto-associative storage of sequences of vectors, as well as of other data structures such as trees.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Integer Sparse Distributed Memory

Sparse distributed memory is an auto associative memory system that stores high dimensional Boolean vectors. Here we present an extension of the original SDM, the Integer SDM that uses modular arithmetic integer vectors rather than binary vectors. This extension preserves many of the desirable properties of the original SDM: auto associativity, content addressability, distributed storage, and r...

متن کامل

Solving Fundamental Problems on Sparse-Meshes

A sparse-mesh, which has PUs on the diagonal of a two-dimensional grid only, is a cost eeective distributed memory machine. Variants of this machine have been considered before, but none of them is so simple and pure as a sparse-mesh. Various fundamental problems (routing, sorting, list ranking) are analyzed, proving that sparse-meshes have a great potential. The results are extended for higher...

متن کامل

An Adaptive Sparse Distributed Memory

Sparse Distributed Memory is a content addressable, associative memory terhnique which relies on close memory items tending to be clustered together, with some abstraction and blurring of details. This paper discusses the limitations of the original model. Then, we propose a method which improve Sparse Distributed Memory efficiency through an adaptive threshold. The results obtained are good an...

متن کامل

Statistical Prediction with Kanerva's Sparse Distributed Memory

A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presented. In conditions of nearor overcapacity, where the associative-memory behavior of the model breaks down, the processing performed by the model can be interpreted as that of a statistical predictor. Mathematical results are presented which serve as the framework for a new statistical viewpoint of ...

متن کامل

Technical Report: Learning with a Sparse Distributed Memory

In this paper we describe a software implementation of a sparse distributed memory in the *Lisp language on a Connection Machine. We use several diierent learning tasks to evaluate the performance of the memory model, including generalization, prediction, and retraining.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011