Fully-digital oscillatory associative memories enabled by non-volatile logic

Calayir, Vehbi; Pileggi, Larry

doi:10.1109/ijcnn.2013.6706925

Cited by 8 publications

(6 citation statements)

References 15 publications

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“…Other results in BZ frequency-based information processing include frequency transformation with a passive barrier [18], frequency band filter [19] and memory [20]. Using frequencies is in line with current developments in oscillatory logic [21], fuzzy logic [11], oscillatory associated memory [22] and computing in arrays of coupled oscillators [23,24]. Therefore, frequencies of oscillations in BZ media will be the focus of this paper.…”

Section: Introductionmentioning

confidence: 86%

Thermal switch of oscillation frequency in Belousov–Zhabotinsky liquid marbles

et al. 2019

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External control of oscillation dynamics in the Belousov–Zhabotinsky (BZ) reaction is important for many applications including encoding computing schemes. When considering the BZ reaction, there are limited studies dealing with thermal cycling, particularly cooling, for external control. Recently, liquid marbles (LMs) have been demonstrated as a means of confining the BZ reaction in a system containing a solid–liquid interface. BZ LMs were prepared by rolling 50 μl droplets in polyethylene (PE) powder. Oscillations of electrical potential differences within the marble were recorded by inserting a pair of electrodes through the LM powder coating into the BZ solution core. Electrical potential differences of up to 100 mV were observed with an average period of oscillation ca 44 s. BZ LMs were subsequently frozen to −1°C to observe changes in the frequency of electrical potential oscillations. The frequency of oscillations reduced upon freezing to 11 mHz cf. 23 mHz at ambient temperature. The oscillation frequency of the frozen BZ LM returned to 23 mHz upon warming to ambient temperature. Several cycles of frequency fluctuations were able to be achieved.

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Section: Introductionmentioning

confidence: 86%

Thermal switch of oscillation frequency in Belousov–Zhabotinsky liquid marbles

et al. 2019

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“…Further investigation of a suitable neuron-like learning mechanism is in progress and will potentially provide Physarum computing with a completely new area of applications. Some preliminary works in this direction include theoretical designs of oscillatory logical systems [29] and logical gates [30], as well as memory [31] and pattern recognition [32].…”

Section: Conclusion and Future Plansmentioning

confidence: 99%

Coupled Physarum-Inspired Memristor Oscillators for Neuron-like Operations

Ntinas

Vourkas

Sirakoulis

et al. 2018

2018 IEEE International Symposium on Circuits and Systems (ISCAS)

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Unconventional computing has been studied intensively even after the appearance of CMOS technology and currently returned to the spotlight because the latter one is about to reach its physical limits, while the always increasing computational power demand requests for novel unconventional computing solutions. In this area, the oscillatory internal motion mechanism of slime mould, namely Physarum Polycephalum, could serve as an alternative concept for the design and development of electronic circuits that exploit the memristive dynamics and simple LC contours to deliver solutions for computationally hard to be solved problems. In this direction, this work presents how bio-inspired memristive LC oscillators with a coupling capacitor can be synchronized to perform the functionalities of a biological neuron, also able to execute more complex computations, aiming to model biological neural systems much more advanced than the neuron-less slime mould biological organism. This work proposes in a plausible and sufficient manner, a connection path between the function mechanism of a simple biological organism and that of complex biological systems, towards unconventional computation with memristors.

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“…The neurons in the network are replaced by oscillators and the output is determined by the phase of each one. There are contributions of mathematical analysis with simulations using phase models for neurons (Hoppensteadt and Izhikevich, 1999;Follmann et al, 2015) as well as reporting implementations with different types of oscillators [phase-locked loops and voltagecontrolled oscillators (Hoppensteadt and Izhikevich, 2000), nonvolatile logic based on magnetic tunnel junctions (Calayir and Pileggi, 2013), micro-electro-mechanical systems and a feedback loop with transconductance amplifiers (Kumar and Mohanty, 2017), comparator and a digital circuit in Jackson et al (2018), CMOS ring oscillators (Csaba et al, 2016), STOs (Popescu et al, 2018), or VO 2 (Shukla et al, 2014;Maffezzoni et al, 2015;Corti et al, 2018)]. The implementations based on VO 2 devices exhibit potential for very low energy computation (Corti et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Oscillatory Neural Networks Using VO2 Based Phase Encoded Logic

et al. 2021

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Nano-oscillators based on phase-transition materials are being explored for the implementation of different non-conventional computing paradigms. In particular, vanadium dioxide (VO2) devices are used to design autonomous non-linear oscillators from which oscillatory neural networks (ONNs) can be developed. In this work, we propose a new architecture for ONNs in which sub-harmonic injection locking (SHIL) is exploited to ensure that the phase information encoded in each neuron can only take two values. In this sense, the implementation of ONNs from neurons that inherently encode information with two-phase values has advantages in terms of robustness and tolerance to variability present in VO2 devices. Unlike conventional interconnection schemes, in which the sign of the weights is coded in the value of the resistances, in our proposal the negative (positive) weights are coded using static inverting (non-inverting) logic at the output of the oscillator. The operation of the proposed architecture is shown for pattern recognition applications.

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Fully-digital oscillatory associative memories enabled by non-volatile logic

Cited by 8 publications

References 15 publications

Thermal switch of oscillation frequency in Belousov–Zhabotinsky liquid marbles

Thermal switch of oscillation frequency in Belousov–Zhabotinsky liquid marbles

Coupled Physarum-Inspired Memristor Oscillators for Neuron-like Operations

Oscillatory Neural Networks Using VO2 Based Phase Encoded Logic

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