多层感知器中的表示与外推

Representation and extrapolation in multilayer perceptrons.

作者信息

Browne Antony

机构信息

School of Computing, Information Systems and Mathematics, London Guildhall University, London UK.

出版信息

Neural Comput. 2002 Jul;14(7):1739-54. doi: 10.1162/08997660260028692.

DOI:10.1162/08997660260028692

PMID:12079554

Abstract

To give an adequate explanation of cognition and perform certain practical tasks, connectionist systems must be able to extrapolate. This work explores the relationship between input representation and extrapolation, using simulations of multilayer perceptrons trained to model the identity function. It has been discovered that representation has a marked effect on extrapolation.

摘要

为了对认知给出充分的解释并执行某些实际任务，联结主义系统必须能够进行外推。这项工作通过对多层感知器进行模拟来探索输入表示与外推之间的关系，这些多层感知器经过训练以对恒等函数进行建模。研究发现，表示对外推有显著影响。