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An accurate analysis method for complex IC analog neural network-based systems using high-level software tools

机译:使用高级软件工具复杂IC模拟神经网络系统的准确分析方法

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For current microelectronic integrated systems, the design methodology involves different steps that end up in the full system simulation by means of electrical and physical models prior to its manufacture. However, the higher the circuit complexity, the more time is required to carry out these simulations, and the convergence of the numerical methods and, hence, the validity of the results are not guaranteed. This paper shows the use of a high-level tool based on Matlab to simulate the operation of an artificial neural network implemented in a mixed analog-digital CMOS process. The proposed tool enables modifying the neural model architecture to adapt its characteristics to those of the electronic system, and provides accurate behavioral models, predicting the microelectronic system operation under different circumstances before its physical implementation.
机译:对于目前的微电子集成系统,设计方法涉及通过在制造之前通过电气和物理模型实现完整系统模拟的不同步骤。然而,电路复杂性越高,执行这些模拟所需的时间越多,数值方法的收敛性,而且,结果不保证结果的有效性。本文示出了基于MATLAB的高级工具的使用来模拟在混合模数CMOS过程中实现的人工神经网络的操作。所提出的工具使修改神经模型架构能够使其特性适应电子系统的特性,并提供准确的行为模型,预测在其物理实现之前在不同情况下的微电子系统操作。

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