A temporal memory network with state-dependent thresholds
Joydeep Ghosh, Siyue Wang · 2002
A fully connected recurrent network that is capable of storing, recalling, and generating a pattern sequence, is presented. This network reproduces a memorized sequence by synchronous updating, and can independently adjust the duration of occurrence of each pattern in the sequence. Such a capability is obtained by using a state dependent threshold for each cell (which reflects the characteristics of the neuron refractory period), and by the use of the hyperbolic tangent activation function rather than a hard limit. Computer simulations highlight the capabilities of the proposed architecture.>