Dynamically weighted time-delay neural networks for functional approximation

被引：0

作者：

Venkatraman, V ^{[1
]}

Rajapakse, JC ^{[1
]}

机构：

[1] Nanyang Technol Univ, Sch Comp Engn, Singapore 2263, Singapore

来源：

IJCNN'01: INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS | 2001年

关键词：

dynamic neural networks; functional approximation; functional MRI; hemodynamic response;

D O I：

10.1109/IJCNN.2001.938811

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The existing multilayer neural networks are not ideally suited for functional approximation of biological activities as they do not capture the time-related dynamics of biological events. We present a dynamically weighted time-delay neural network (DWTDNN) which is more suited for computations on temporal patterns from biological events. We use this network for modeling the time-series data from fMRI experiments and compare the results with those obtained using existing models of fMRI response.

引用

页码：2768 / 2773

页数：6

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