A MODULAR T-MODE DESIGN APPROACH FOR ANALOG NEURAL NETWORK HARDWARE IMPLEMENTATIONS

A modular transconductance-mode (T-mode) design approach is presented for analog hardware implementations of neural networks. This design approach is used to build a modular bidirectional associative memory (BAM) network. We will show that the size of the whole system can be increased by interconnecting more modular chips together. Also, we will show that by changing the interconnection strategy different neural network systems can be implemented, such as a Hopefield network, a winner-take-all network, a simplified ART1 network, or a constrained optimization network. Experimentally measured results from CMOS 2-mu-m double-metal, double-polysilicon prototypes (MOSIS) are presented.