Weight-control strategy for programmable CNN chips

This paper describes a hybrid weight-control strategy for the VLSI realization of programmable cellular neural nets (CNNs), based on automatic adaptation of analog control signals to levels specified by digital words. This approach merges the advantages of digital and analog programmability, achieving low areas and reduced number of control lines, simplifying the control and storage of the weight values and eliminating their dependency on global process-parameter variations