Synaptic behaviour in ZnO–rGO composites thin film memristor

Khanal, Gaurav Mani; Acciarito, Simone; Cardarilli, G.C.; Chakraborty, Abhisek; Nunzio, L.D.; Fazzolari, Rocco; Cristini, A.; Re, M.; Susi, Gianluca

doi:10.1049/el.2016.3655

Cited by 21 publications

(10 citation statements)

References 13 publications

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“…Interestingly, Viriyopase et al [17] have shown that in these networks the stability is facilitated when spike timing dependent plasticity (STDP) is implemented in the synapses, which is also capable to convert slave synchrony to driven synchrony, and thus to expand the possibility of reaching such a stable regime. This suggests for future works the realization of the dynamical relaying motif with plastic synapses [28]. Fig.6: Pipeline of the implemented method for the validation of the circuit Neural networks are being used today for a plenty of application, ranging from classification [29], [30], prediction [31]- [34], or optimization [35] problems, as well as for the emulation of brain dynamics [36], [37].…”

Section: Resultsmentioning

confidence: 99%

Towards Neuro-Inspired Electronic Oscillators Based on The Dynamical Relaying Mechanism

Susi

Acciarito

Pascual

et al. 2019

Int. J. Adv. Sci. Eng. Inf. Technol.

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Electronic oscillators are used for the generation of both continuous and discrete signals, playing a fundamental role in today's electronics. In both contexts, these systems require stringent performances such as spectral purity, low phase noise, frequency and temperature stability. In state of the art oscillators the preservation of some of these aspects is jeopardized by specific critical issues, e.g., the sensitivity to load capacitance or the component aging over time. This leaves room for the search of new technologies for their realization. On the other hand, in the last decade electronics has been influenced by a growing number of neuro-inspired mechanisms, which allowed for alternative techniques aimed at solving some classical critical issues. In this paper we present an exploratory study for the development of electronic oscillators based on the neuro-inspired mechanism dynamical relaying, which relies on a structure composed of three delay coupled units (as neurons or even neuron populations) able to resonate and self-organise to generate and maintain a given rhythm with great reliability over a considerable parameter range, showing robustness to noise. We used the recent leaky integrated and fire with latency (LIFL) as neuron model. We have initially developed the mathematical model of the neuro-inspired oscillator, and implemented it using Matlab®; then, we have realized the schematic of such system in PSpice®. Finally, the model has been validated to verify whether it observes the fundamental properties of the dynamical relaying mechanisms described in computational neuroscience studies, and if the circuit implementation presents the same behaviour of the mathematical model. Validation results suggest that the dynamical relaying mechanism can be proficuously taken in consideration as alternative strategy for the design of electronic oscillators.Keywords-LIFL neuron model; electronic oscillators; dynamical relaying; spiking neural networks.

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Section: Resultsmentioning

confidence: 99%

Towards Neuro-Inspired Electronic Oscillators Based on The Dynamical Relaying Mechanism

Susi

Acciarito

Pascual

et al. 2019

Int. J. Adv. Sci. Eng. Inf. Technol.

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“…To each subsequences can be associated a probability (see Table 1) considering that the string is composed by a total number of 10 possible subsequences of 2 characters (since L = 11). Using (3)…”

Section: A N-th Order Absolute Entropymentioning

confidence: 99%

“…Te micro-electro-mechanical systems (MEMS) technology has encountered a tremendous evolution in the last decades [1]- [3]. The reached integration level permits us…”

Section: Introductionmentioning

confidence: 99%

An Entropy Evaluation Algorithm to Improve Transmission Efficiency of Compressed Data in Pervasive Healthcare Mobile Sensor Networks

et al. 2020

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Data transmission is the most critical operation for mobile sensors networks in term of energy waste. Particularly in pervasive healthcare sensors network it is paramount to preserve the quality of service also by means of energy saving policies. Communication and data transmission are among the most critical operation for such devises in term of energy waste. In this paper we present a novel approach to increase battery lifespan by means of shorter transmission due to data compression. On the other hand, since this latter operation has a non-neglectable energy cost, we developed a compression efficiency estimator based on the evaluation of the absolute and relative entropy. Such algorithm provides us with a fast mean for the evaluation of data compressibility. Since mobile wireless sensor networks are prone to battery discharge-related problems, such an evaluation can be used to improve the electrical efficiency of data communication. In facts the developed technique, due to its independence from the string or file length, is extremely robust both for small and big data files, as well as to evaluate whether or not to compress data before transmission. Since the proposed solution provides a quantitative analysis of the source's entropy and the related statistics, it has been implemented as a preprocessing step before transmission. A dynamic threshold defines whether or not to invoke a compression subroutine. Such a subroutine should be expected to greatly reduce the transmission length. On the other hand a data compression algorithm should be used only when the energy gain of the reduced transmission time is presumably greater than the energy used to run the compression software. In this paper we developed an automatic evaluation system in order to optimize the data transmission in mobile sensor networks, by compressing data only when this action is presumed to be energetically efficient. We tested the proposed algorithm by using the Canterbury Corpus as well as standard pictorial data as benchmark test. The implemented system has been proven to be time-inexpensive with respect to a compression algorithm. Finally the computational complexity of the proposed approach is virtually neglectable with respect to the compression and transmission routines themselves.

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“…Metal-oxide-based memristive devices have attracted much attention due to their ability to process and store information with minimum power requirements, and for this reason, soon, they could replace transistor-based flash memory [1][2][3][4][5][6][7]. Memristors can be integrated into a highly dense crossbar network array to implement the interconnection of a high number of CMOS neurons emulating spike-based learning [8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

“…Correspondingly, we obtain a voltage or current-controlled memristor. The most important characteristic of the memristor is the pinched hysteresis loop in its current-voltage (I−V) curve, when the device is connected to a varying input voltage or current, pinched hysteresis makes a memristor a passive and fourth fundamental circuit element besides the resistor, capacitor, and inductor [9,10,17]…”

Section: Introductionmentioning

confidence: 99%

Memristive and Memory Impedance Behavior in a Photo-Annealed ZnO–rGO Thin-Film Device

et al. 2020

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An oxygen-rich ZnO-reduced graphene oxide (rGO) thin film was synthesized using a photo-annealing technique from zinc precursor (ZnO)–graphene oxide (GO) sol–gel solution. X-ray diffraction (XRD) results show a clear characteristic peak corresponding to rGO. The scanning electron microscope (SEM) image of the prepared thin film shows an evenly distributed wrinkled surface structure. Transition Metal Oxide (TMO)-based memristive devices are nominees for beyond CMOS Non-Volatile Memory (NVRAM) devices. The two-terminal Metal–TMO (Insulator)–Metal (MIM) memristive device is fabricated using a synthesized ZnO–rGO as an active layer on fluorine-doped tin oxide (FTO)-coated glass substrate. Aluminum (Al) is deposited as a top metal contact on the ZnO–rGO active layer to complete the device. Photo annealing was used to reduce the GO to rGO to make the proposed method suitable for fabricating ZnO–rGO thin-film devices on flexible substrates. The electrical characterization of the Al–ZnO–rGO–FTO device confirms the coexistence of memristive and memimpedance characteristics. The coexistence of memory resistance and memory impedance in the same device could be valuable for developing novel programmable analog filters and self-resonating circuits and systems.

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Synaptic behaviour in ZnO–rGO composites thin film memristor

Cited by 21 publications

References 13 publications

Towards Neuro-Inspired Electronic Oscillators Based on The Dynamical Relaying Mechanism

Towards Neuro-Inspired Electronic Oscillators Based on The Dynamical Relaying Mechanism

An Entropy Evaluation Algorithm to Improve Transmission Efficiency of Compressed Data in Pervasive Healthcare Mobile Sensor Networks

Memristive and Memory Impedance Behavior in a Photo-Annealed ZnO–rGO Thin-Film Device

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