A novel cellular neural network (CNN) cell and its circuit realization are proposed. The theory of the multi-nested universal cell is applied, and the nonmonotonic current-voltage characteristic of resonant tunneling diodes (RTD) is exploited to achieve a high functionality. The proposed cell has the potential of implementing arbitrary local Boolean functions with n inputs. The cell has a complexity of only O(n) in the number of devices and template elements. For comparison, the digital n-to-1 multiplexor, a functionally equivalent system has a complexity of O(2/sup n/). A simple, piecewise-linear mathematical model is derived and used to evaluate the functional capabilities of the RTD-CNN cell. The model was proved to be accurate enough, and only minor tuning of some of the parameters is necessary to achieve the same functionality using a Spice simulation of the same circuit, which is based on more refined physical device models.
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机译:提出了一种新型的细胞神经网络(CNN)单元及其电路实现。应用多嵌套通用电池的理论,并利用谐振隧穿二极管(RTD)的非单调电流-电压特性来实现高功能性。所提出的单元具有用n个输入实现任意局部布尔函数的潜力。在设备和模板元素的数量上,该单元的复杂度仅为O(n)。为了进行比较,功能上等效的数字n对1多路复用器的复杂度为O(2 / sup n /)。推导了一个简单的分段线性数学模型,并将其用于评估RTD-CNN单元的功能。该模型已被证明足够准确,并且使用相同电路的Spice仿真(基于更精确的物理设备模型),只需对某些参数进行较小的调整即可实现相同的功能。
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