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

机译:使用高级软件工具的基于复杂IC模拟神经网络的系统的精确分析方法

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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:对于当前的微电子集成系统,设计方法涉及不同的步骤,最终会在制造之前通过电气和物理模型对整个系统进行仿真。但是,电路复杂度越高,进行这些仿真所需的时间就越多,并且数值方法的收敛性也因此而得不到保证。本文展示了使用基于Matlab的高级工具来模拟在混合模数CMOS工艺中实现的人工神经网络的操作。所提出的工具能够修改神经模型架构以使其特性适应电子系统的特性,并提供精确的行为模型,从而在物理实现之前预测微电子系统在不同情况下的运行情况。

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