Conjunctoids: Statistical learning modules for binary events

Robert J. Jannarone; Kai F. Yu; Yoshiyasu Takefuji

doi:10.1016/0893-6080(88)90006-8

Conjunctoids: Statistical learning modules for binary events

Robert J. Jannarone, Kai F. Yu, Yoshiyasu Takefuji

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

A general family of fast and efficient neural network learning modules for binary events is introduced. The family subsumes probabilistic as well as functional event associations; subsumes all levels of input/output association; yields truly parallel learning processes; provides for optimal parameter estimation; points toward a workable description of optimal model performance; and yields procedures that are simple and fast enough to be serious candidates for reflecting both neural functioning and real time machine learning. Examples as well as operational details are provided.

Original language	English
Pages (from-to)	325-337
Number of pages	13
Journal	Neural Networks
Volume	1
Issue number	4
DOIs	https://doi.org/10.1016/0893-6080(88)90006-8
Publication status	Published - 1988
Externally published	Yes

Keywords

Binary neural networks
Conjunctive measurement
Machine learning
Neurocomputing
Nonlinear neural networks
Parallel distributed processing
Statistical pattern recognition

ASJC Scopus subject areas

Cognitive Neuroscience
Artificial Intelligence

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10.1016/0893-6080(88)90006-8

Cite this

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title = "Conjunctoids: Statistical learning modules for binary events",

abstract = "A general family of fast and efficient neural network learning modules for binary events is introduced. The family subsumes probabilistic as well as functional event associations; subsumes all levels of input/output association; yields truly parallel learning processes; provides for optimal parameter estimation; points toward a workable description of optimal model performance; and yields procedures that are simple and fast enough to be serious candidates for reflecting both neural functioning and real time machine learning. Examples as well as operational details are provided.",

keywords = "Binary neural networks, Conjunctive measurement, Machine learning, Neurocomputing, Nonlinear neural networks, Parallel distributed processing, Statistical pattern recognition",

author = "Jannarone, {Robert J.} and Yu, {Kai F.} and Yoshiyasu Takefuji",

year = "1988",

doi = "10.1016/0893-6080(88)90006-8",

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pages = "325--337",

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T2 - Statistical learning modules for binary events

AU - Jannarone, Robert J.

AU - Yu, Kai F.

AU - Takefuji, Yoshiyasu

PY - 1988

Y1 - 1988

N2 - A general family of fast and efficient neural network learning modules for binary events is introduced. The family subsumes probabilistic as well as functional event associations; subsumes all levels of input/output association; yields truly parallel learning processes; provides for optimal parameter estimation; points toward a workable description of optimal model performance; and yields procedures that are simple and fast enough to be serious candidates for reflecting both neural functioning and real time machine learning. Examples as well as operational details are provided.

AB - A general family of fast and efficient neural network learning modules for binary events is introduced. The family subsumes probabilistic as well as functional event associations; subsumes all levels of input/output association; yields truly parallel learning processes; provides for optimal parameter estimation; points toward a workable description of optimal model performance; and yields procedures that are simple and fast enough to be serious candidates for reflecting both neural functioning and real time machine learning. Examples as well as operational details are provided.

KW - Binary neural networks

KW - Conjunctive measurement

KW - Machine learning

KW - Neurocomputing

KW - Nonlinear neural networks

KW - Parallel distributed processing

KW - Statistical pattern recognition

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VL - 1

SP - 325

EP - 337

JO - Neural Networks

JF - Neural Networks

IS - 4

ER -

Conjunctoids: Statistical learning modules for binary events

Abstract

Keywords

ASJC Scopus subject areas

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