Architectural Design of Multiplicative type-II Fuzzy Cellular Neural Network in CMOS Technology

The architecture of multiplicative type-II cellular neural networks with fuzzy (FCNN) is proposed, which is with local connectivity advantageous suitable implemented for VLSI. The fuzzy AND and fuzzy OR morphological operators in the Type II FCNN can be operated by Min and Max operations for the feel forward template from neighbouring cell of input image in dynamic parallel processing. Base on the proposed FCNN structure that the neuron, Min/Max, analog multiplier, transfer and control circuits are adopted and verified by the HSPICE. The desired experimental chip of 3 times 3 multiplicative type-II FCNN is fabricated using TSMC 0.35 mum 2P4M CMOS technology. The measurement results have successfully verified the correct function of FCNN. There have a great potential in the VLSI implementation of neural network systems for binary and gray-level patterns in image- processing for consume electronic applications.