共振穿隧二極體為基礎的細胞神經網路(resonant-tunneling-diode-based cellular neural network, 以下簡稱RTD-based CNN[1])在1999 年提出時，相較於傳統的CNN 而言，RTD-based CNN 在電子電路設計上具有結構簡單、速度快、建構輕鬆的特性。因此在奈米電子電路有極佳的應用。有關RTD-based CNN 的研究著重在設計與所表現行為兩方面，兩者都與RTD-based CNN 本身的參數有關。其數學模型是一個多維度的 piecewise-linear 的常微分方程—與傳統CNN 的數學模型類似。因此，RTD-based CNN 被預期有複雜且有趣的動態行為。我們將對適當範圍的參數，調查其動態行為隨著參數的變化的現象，包括分歧、渾沌等現象。並解釋其成因。 The use of resonant tunneling diode in application to cellular neural networks (CNN) has been reported in [1] and is called RTD-based CNN. The RTD-based CNN has the advantage of structural simplicity, relative ease of fabrication, high speed and design flexibility and is hence an excellent candidate for nanoelectronics application. The template design and dynamical behavior of RTD-based CNN are two issues to be concerned. Similar to CNN, the mathematical model of RTD-based CNN is a set of coupled piecewise-linear differential equation and is therefore expect to own complex and interesting behavior. We will investigate the variation of of RTD-based CNN』s dynamical behavior such like bifurcation and route to chaos while the parameters changes over a suitable range. We will also try to give an explanation to observed phenomenon.
