A digital circuit design of state-space recurrent neural networks
Che‐Wei Lin, Jeen-Shing Wang · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · 2008
This paper presents a digital circuit design of a state-space recurrent neural network (RNN). The proposed digital circuit design separates the datapath of the state-space RNN into a linear subcircuit and a nonlinear subcircuit. The linear subcircuit is realized by a matrix-vector multiplier while the nonlinear subcircuit by a customized nonlinear function computing unit. The throughput rate of the proposed RNN circuit is 36060.5 times faster than that of the software simulation using MATLABreg. The proposed state-space RNN digital design methodology not only possesses the advantages including high computing speed, small area and portability, but also increases the possibility of using the digital RNN circuit in real-world dynamic problems.