Memory Storage Systems Utilizing Chaotic Attractor-Merging Bifurcation
Memory Storage Systems Utilizing Chaotic Attractor-Merging Bifurcation
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DOI：
10.1109/access.2022.3149055
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发表时间：
2022
期刊：
影响因子：
3.9
通讯作者：
S. Nobukawa;Nobuhiko Wagatsuma;H. Nishimura;Keiichiro Inagaki;Teruya Yamanishi
中科院分区：
文献类型：
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作者：
S. Nobukawa;Nobuhiko Wagatsuma;H. Nishimura;Keiichiro Inagaki;Teruya Yamanishi
在具有屏障/阈值的非线性动力学系统中，通过适当的加性噪声（随机共振）来增强对弱外部输入信号的信号响应。近年来，在随机共振的应用中的进展表明，加性噪声的存在使得即使在极低功耗的情况下也提高了使用双稳态振荡的存储器元件中的存储器存储功能。通过不限制加性噪声，确定性混沌（内部波动）引起类似的现象，称为混沌共振。非线性动力学系统中存在混沌共振现象，并伴随着混沌-混沌不稳定性，即混沌轨道通过吸引子合并分岔在分离的吸引子区域间间歇性地跃迁。以前，在各种类型的系统中报道了比随机共振更高的混沌共振灵敏度。在这项研究中，我们假设，混沌共振为基础的存储设备可以存储信息与较低的功耗比随机共振为基础的设备。为了证明这一假设，我们诱导吸引子合并分岔的立方映射系统，这是最简单的模型出现的混沌共振。之后，我们在无噪声系统下调整内部系统参数作为混沌共振，并施加类似于诱导随机共振的条件的随机噪声。研究结果表明，即使在较弱的记忆存储输入信号下，前者也比后者表现出更高的记忆存储能力。利用混沌共振的方法可以促进迄今为止仅限于随机共振应用的存储器件的发展。
In nonlinear dynamical systems with barriers/thresholds, the signal response against a weak external input signal is enhanced by an appropriate additive noise (stochastic resonance). In recent years, progress in the application of stochastic resonance shows that the existence of additive noise heightens the memory storage functions in memory elements using bistable oscillations even with extremely low power consumption. By not restricting the additive noise, the deterministic chaos (an internal fluctuation) induces a similar phenomenon known as chaotic resonance. Chaotic resonance appears in nonlinear dynamical systems and is accompanied by chaos–chaos intermittency, where the chaotic orbit intermittently transitions among separated attractor regions through attractor-merging bifurcation. Previously, a higher chaotic resonance sensitivity than that of stochastic resonance was reported in various types of systems. In this study, we hypothesize that chaotic-resonance-based memory devices can store information with lower power consumption than that of stochastic-resonance-based devices. To prove this hypothesis, we induced attractor-merging bifurcation in a cubic map system, which is the simplest model for the emergence of chaotic resonance. Thereafter, we adjusted the internal system parameter under a noise-free system as the chaotic resonance and applied stochastic noise similar to the condition for inducing stochastic resonance. The results of this study reveal that, even with weaker memory storage input signals, the former exhibits a higher memory storage capability than the latter. The approach using chaotic resonance could facilitate the development of memory devices that were hitherto restricted to the application of stochastic resonance.