Sparse distributed memory (SDM) is a mathematical model of human long-term memory introduced by Pentti Kanerva in 1988 while he was at NASA Ames Research...

example, in sparse distributed memory (SDM), the patterns encoded by neural networks are used as memory addresses for content-addressable memory, with "neurons"...

1126/science.1225266. PMID 23197532. S2CID 1673514. Denning, Peter J. "Sparse distributed memory." (1989).Url: https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa...

stimuli. Theoretical work on sparse distributed memory has suggested that sparse coding increases the capacity of associative memory by reducing overlap between...

system. In IDA, these two memories are implemented computationally using a modified version of Kanerva’s sparse distributed memory architecture. Learning...

the long-term memory effectively acts as a (dynamic) knowledge base and the output is a textual response. In sparse distributed memory or hierarchical...

several modules, including variants of the Copycat Architecture, sparse distributed memory, the schema mechanism, the Behavior Net, and the subsumption architecture...

mathematical model of sparse distributed memory This disambiguation page lists articles associated with the title Genetic memory. If an internal link led...

storage, or file system Sparse distributed memory Tuple space "K. Pagiamtzis* and A. Sheikholeslami, Content-addressable memory (CAM) circuits and architectures:...

genetic memory refers to an artificial neural network combination of genetic algorithm and the mathematical model of sparse distributed memory. It can...

drafts model of consciousness Neural correlates of consciousness Sparse distributed memory Baars 1998. sfn error: no target: CITEREFBaars1998 (help) Baars...

and the originator of the sparse distributed memory model. He is responsible for relating the properties of long-term memory to mathematical properties...

technique useful for dimensionality reduction Sparse distributed memory – Mathematical model of memory Visual perception – Ability to interpret the surrounding...

categorically-organized fashion." Memory semantics Sparse distributed memory Semantic similarity McRae, Ken; Jones, Michael (2013). "Semantic Memory". In Reisberg, Daniel...

Eigenvalues and eigenvectors Inverted index Nearest neighbor search Sparse distributed memory w-shingling Berry, Michael W.; Drmac, Zlatko; Jessup, Elizabeth...

neuroscience Neural Darwinism Predictive coding Predictive learning Sparse distributed memory Metz, Cade (October 15, 2018). "A new view of how we think". The...

Range search Similarity learning Singular value decomposition Sparse distributed memory Statistical distance Time series Voronoi diagram Wavelet Cayton...

quantization Liquid state machine Neocognitron Neural gas Sparse coding Sparse distributed memory Topological data analysis Kohonen, Teuvo (January 2013)...

Singular value decomposition – Matrix decomposition Sparse distributed memory – Mathematical model of memory Wavelet compression – Mathematical technique used...

reduction Sparse distributed memory – Mathematical model of memory Khan, J. I. (1998). "Characteristics of multidimensional holographic associative memory in...

Mahalanobis distance Mannheim distance Sørensen similarity index Sparse distributed memory Word ladder Waggener, Bill (1995). Pulse Code Modulation Techniques...

series of evaluations of computational semantic analysis systems Sparse distributed memory Taxonomy (general) Unified Medical Language System (UMLS) Word-sense...

(ISBN 1-55953-280-7) Alan Turing: The Enigma by Andrew Hodges, 1983. (Preface) Sparse Distributed Memory by Pentti Kanerva, Bradford Books/MIT Press, 1988. (Foreword)...

software system development method originally written by PANDATA. Sparse distributed memory Space-division multiplexing Brown Field Municipal Airport, San...

representation of language, originates from the work of Pentti Kanerva on sparse distributed memory, and can be described as an incremental formulation of a random...

representations assume useful properties. Examples are regularized autoencoders (sparse, denoising and contractive autoencoders), which are effective in learning...

scalability. In the following, shared and distributed memory architectures are considered. In the case of a shared memory model, the graph representations used...

supports flexible schemas and efficiently handles data models with numerous sparse columns. The system is optimized for applications with well-defined data...

implementation. Elemental Elemental is an open source software for distributed-memory dense and sparse-direct linear algebra and optimization. HASEM is a C++ template...

time scales. Engram (neuropsychology) Hierarchical temporal memory Sparse distributed memory Semon RW (1923). Mnemonic psychology. London: George Allen...