Analog integrated circuits and signal processing vol:15 issue:3 pages:251-262
Analog parallel signal processing systems, like cellular neural networks (CNN's), intrinsically have a high potential for perception-like signal processing tasks. The robust design of analog VLSI requires a good understanding of the capabilities as well as the limitations of analog signal processing. Implementation-oriented theoretical methods are described to compute the effect of all types circuit non-idealities with random or systematic causes on the static and dynamical behavior of CNN's and to derive specifications for the cell circuit building blocks. The fundamental impact of transistor mismatch on the trade-off between the speed, accuracy and power performance of CNN chips is demonstrated. A design methodology taking into account the effect of transistor mismatch is proposed and experimental results of a CNN chip implementation designed with this method are discussed.