Parameterization of connectionist models.

Journal article

Abstract:: We present a method for estimating parameters of connectionist models that allows the model's output to fit as closely as possible to empirical data. The method minimizes a cost function that measures the difference between statistics computed from the model's output and statistics computed from the subjects' performance. An optimization algorithm finds the values of the parameters that minimize the value of this cost function. The cost function also indicates whether the model's statistics a...
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Institution:

University of Oxford

Division:

MSD

Department:

Clinical Neurosciences

Role:

Author

Role:

Author

Journal:: Behavior research methods, instruments, and computers : a journal of the Psychonomic Society, Inc
Volume:: 36
Issue:: 4
Pages:: 732-741
Publication date:: 2004-11-01
DOI:: 10.3758/bf03206554
EISSN:: 1532-5970
ISSN:: 0743-3808

Language:: English
Keywords:: Neural Networks (Computer)

Humans

Models, Psychological

Algorithms

Reaction Time

Attention

Psychology
Pubs id:: pubs:420771
UUID:: uuid:395548fa-0518-4d37-a658-0f0789d642e2
Local pid:: pubs:420771
Source identifiers:: 420771
Deposit date:: 2013-11-16

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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