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TopChaotic Neural Networks And Incremental Learning
The incremental learning was developed by using the chaotic neurons. The chaotic neurons and the chaotic neural networks were proposed by Aihara (Aihara, Tanabe &Toyoda, 1990).
We presented the incremental learning that provides an associative memory (Asakawa, Deguchi & Ishii, 2001; Deguchi & Ishii, 2004; Deguchi, Fukuta & Ishii, 2013; Deguchi, Matsuo, Kimura & Ishii, 2009-07; Deguchi, Takahashi & Ishii, 2014). The network type is an interconnected network, in which each neuron receives one external input, and is defined as follows (Aihara, Tanabe & Toyoda, 1990):
,
(1),
(2),
(3),
(4) where
is the output of the
-th neuron at time
,
is the output sigmoid function described below in (5),
,
,
are the time decay constants,
is the input to the
-th neuron at time
,
is the weight for external inputs,
is the size—the number of the neurons in the network,
is the connection weight from the
-th neuron to the
-th neuron, and
is the parameter that specifies the relation between the neuron output and the refractoriness.