Expectation and variance of item resemblance distributions in a convolution-correlation model of distributed memory

DOI10.1016/0022-2496(88)90036-3zbMath0666.92025OpenAlexW2072769322MaRDI QIDQ1117165

Elke U. Weber

Publication date: 1988

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0022-2496(88)90036-3

zbMATH Keywords

distributed processingconvolution-correlation modelsdistributed associative memorysignal recognition

Mathematics Subject Classification ID

Artificial intelligence (68T99) Mathematical psychology (91E99)

Related Items (5)

Sparse attentional subsetting of item features and list-composition effects on recognition memory ⋮ Adding a bias to vector models of association memory provides item memory for free ⋮ Modelling constituent order despite symmetric associations in memory ⋮ Item and associative information in a distributed memory model ⋮ Judgements of frequency and recency in a distributed memory model.

Cites Work

• Unnamed Item
• Unnamed Item
• Some algebraic relations between involutions, convolutions, and correlations, with applications to holographic memories
• Similarity in a distributed memory model
• A simple neural network generating an interactive memory
• On the Exact Variance of Products
• The Variance of the Product of K Random Variables
• Convolution and correlation algebras
• Neural networks and physical systems with emergent collective computational abilities.
• On the Exact Covariance of Products of Random Variables
• Microscopy by reconstructed wave-fronts
• Microscopy by Reconstructed Wave Fronts: II

This page was built for publication: Expectation and variance of item resemblance distributions in a convolution-correlation model of distributed memory