A Locally Active Memristor and Its Application in a Chaotic Circuit

Jin, Peipei; Wang, Guangyi; Iu, Herbert Ho-Ching; Fernando, Tyrone

doi:10.1109/tcsii.2017.2735448

Cited by 69 publications

(42 citation statements)

References 16 publications

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“…Driven by a bipolar periodic signal, the memristor exhibits a hysteresis loop pinched at the origin in the current-voltage plane. An integer-order nonlinear voltage-controlled memristor is stated as follows [30]:…”

Section: Fractional-order Locally Activementioning

confidence: 99%

“…where v and i are the voltage and current of the memristor, respectively, x m is the internal state of the memristor and W(x m ) � x 2 m − x m − 1 is the memductance, and p 1 , p 2 , p 3 , and p 4 are the system parameters. By using the trial and error method [30], the parameters are decided as p 1 � 1.8, p 2 � 3.9, p 3 � 1.4, and p 4 � 1.5. Considering the memory effect from the memristor, a fractional-order voltage-controlled memristor M α corresponding to (1) is modeled as follows:…”

Section: Fractional-order Locally Activementioning

confidence: 99%

“…Besides the memristor can be modeled by the fractionalorder derivative, the capacitor and the inductor can also be modeled by the fractional-order derivative due to the memory effect [12,32]. With the fractional-order locally active memristor, a fractional-order memristive circuit is generalized from an integer-order memristive circuit [30], as shown in Figure 1…”

Section: Fractional-order Memristor-based Systemmentioning

confidence: 99%

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Complex Dynamical Behaviors of a Fractional‐Order System Based on a Locally Active Memristor

Bao

Shi

et al. 2019

Complexity

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A fractional-order locally active memristor is proposed in this paper. When driven by a bipolar periodic signal, the generated hysteresis loop with two intersections is pinched at the origin. The area of the hysteresis loop changes with the fractional order. Based on the fractional-order locally active memristor, a fractional-order memristive system is constructed. The stability analysis is carried out and the stability conditions for three equilibria are listed. The expression of the fractional order related to Hopf bifurcation is given. The complex dynamical behaviors of Hopf bifurcation, period-doubling bifurcation, bistability and chaos are shown numerically. Furthermore, the bistability behaviors of the different fractional order are validated by the attraction basins in the initial value plane. As an alternative to validating our results, the fractional-order memristive system is implemented by utilizing Simulink of MATLAB. The research results clarify that the complex dynamical behaviors are attributed to two facts: one is the fractional order that affects the stability of the equilibria, and the other is the local activeness of the fractional-order memristor.

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Section: Fractional-order Locally Activementioning

confidence: 99%

Section: Fractional-order Locally Activementioning

confidence: 99%

Section: Fractional-order Memristor-based Systemmentioning

confidence: 99%

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Complex Dynamical Behaviors of a Fractional‐Order System Based on a Locally Active Memristor

Bao

Shi

et al. 2019

Complexity

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“…The locally-active NbO 2 Mott memristor has been used in the Hopfield network for generating oscillation and finding a global minimum during a constrained search [Kumar et al, 2017]. Jin et al [2018] proposed a locally-active memristor model and constructed a chaotic attractor with the memristor. Very recently, Chang et al [2018] reported a new bistable bilocally-active memristor and its associated oscillator circuit.…”

Section: Introductionmentioning

confidence: 99%

Switching Characteristics of a Locally-Active Memristor with Binary Memories

Ying

Wang

Dong

et al. 2019

Int. J. Bifurcation Chaos

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A number of important applications would benefit from the introduction of locally-active memristors, which is defined to be any memristor that exhibits negative differential memristance for at least a voltage or a current applied to the memristor. Two leading examples are emerging nonvolatile memory based on memristor-based crossbar array architectures, and neural networks that exhibit improved computational complexity when operated at the edge of chaos. In this paper, a novel locally-active memristor model is presented for exploring the nonvolatile and switching mechanism of the memristor and the influence of local activity on the complexity of nonlinear circuits. We find that the memristor possesses three locally-active regions in its DC [Formula: see text]–[Formula: see text] plot and two asymptotically stable states (equilibrium points) on its power-off plot (POP) where voltage [Formula: see text], implying that the memristor is bistable, which can be used as a nonvolatile binary memory or binary switch. We also find the mechanism and the rule of switching between the two stable states by applying a single square voltage pulse of appropriate pulse width and pulse amplitude. We show that it is always possible to switch from one stable state to another of the memristor with an appropriate pulse amplitude and a pulse width, and that there is a trade-off between the voltage pulse amplitude and the pulse width for the faster switching between the two equilibrium points. We also show that fast switching between the two states is possible by using a periodic bipolar narrow pulse sequence. Local activity depends on the capability of a memristor circuit to amplify infinitesimal fluctuations in energy. Based on this principle, we designed a simplest chaotic oscillator that utilizes only three components in parallel: the proposed locally-active memristor, a linear capacitor and an inductor, which can oscillate around an equilibrium point located on its DC [Formula: see text]–[Formula: see text] plot. Its dynamic characteristics are verified by theoretical analyses, simulations and DSP experiments.

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“…However, deterministic circuits can be very simple in design and the chaotic process can produce time series, which seem to be unpredictable to the observer, due to the sophisticated dynamic behavior in the limited observation time [43]. It turns out that chaotic systems described with simple linear one dimensional formulas can produce very complex circuit behavior [44]. In such systems, the "unpredictability" results from the sensitivity to an initial condition, which affects the circuit's state in time.…”

Section: Introductionmentioning

confidence: 99%

Chaos-Based Physical Unclonable Functions

Gołofit

Wieczorek

2019

Applied Sciences

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The concept presented in this paper fits into the current trend of highly secured hardware authentication designs utilizing Physically Unclonable Functions (PUFs) or Physical Obfuscated Keys (POKs). We propose an idea that the PUF cryptographic keys can be derived from a chaotic circuit. We point out that the chaos theory should be explored for the sake of PUFs as a natural mechanism of amplifying random process variations of digital circuits. We prove the idea based on a novel design of a chaotic circuit, which utilizes time in a feedback loop as an analog continuous variable in a purely digital system. Our design is small and simple, and therefore feasible to implement in inexpensive reprogrammable devices (not equipped with digital clock manager, programmable delay line, phase locked loop, RAM/ROM memory, etc.). Preliminary tests proved that the chaotic circuit PUFs work in both advanced Field-Programmable Gate Arrays (FPGAs) as well as simple Complex Programmable Logic Devices (CPLDs). We showed that different PUF challenges (slightly different implementations based on variations in elements placement and/or routing) have provided significantly different keys generated within one CPLD/FPGA device. On the other hand, the same PUF challenges used in a different CPLD/FPGA instance (programmed with precisely the same bit-stream resulting in exactly the same placement and routing) have enhanced differences between devices resulting in different cryptographic keys.

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A Locally Active Memristor and Its Application in a Chaotic Circuit

Cited by 69 publications

References 16 publications

Complex Dynamical Behaviors of a Fractional‐Order System Based on a Locally Active Memristor

Complex Dynamical Behaviors of a Fractional‐Order System Based on a Locally Active Memristor

Switching Characteristics of a Locally-Active Memristor with Binary Memories

Chaos-Based Physical Unclonable Functions

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