Generalisation of action sequences in RNNPB networks with mirror properties
Generalisation of action sequences in RNNPB networks with mirror properties
复制标题
具有镜像特性的 RNPB 网络中动作序列的泛化
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
I. Sprinkhuizen
中科院分区：
文献类型：
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作者：
R. Cuijpers;Floran Stuijt;I. Sprinkhuizen
The human mirror neuron system (MNS) is supposed to be involved in recognition of observed action sequences. However, it remains unclear how such a system could learn to recognise a large variety of action sequences. Here we investigated a neural network with mirror properties, the Recurrent Neural Network with Parametric Bias (RNNPB). We show that the network is capable of recognising noisy action sequences and that it is capable of generalising from a few learnt examples. Such a mechanism may explain how the human brain is capable of dealing with an infinite variety of action sequences.
