A variable bandwidth memristor‐based Legendre Optimum low pass filter for radio frequency applications

Onyejegbu, Elochukwu; Zhumabay, Zhazira; Marzuki, Arjuna; Ukaegbu, Ikechi Augustine

doi:10.1002/eng2.12513

Cited by 4 publications

(2 citation statements)

References 39 publications

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“…Another instance of a tunable first-order active highpass filter employing a TiO 2 memristor is designed in [23]. Commercial KnowM memristors are recommended for RF passive filter implementations, as illustrated in [24], where the lowpass filter bandwidth can be adjusted by varying the memristance value.…”

Section: Introductionmentioning

confidence: 99%

The Dynamic Tunability of Memristor-Based Active Filters

Marković,

Potrebić Ivaniš,

Tošić

2023

Micromachines

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When the memristor was fabricated for the first time, it launched an entirely new field of research. Many of the published papers regarding memristors are primarily theoretical and are based on computer simulations. Some recent papers analyze the memristor’s programming circuits, but to the best of the authors’ knowledge, no memristor has been embedded into a commercial analog circuit. This paper is practically oriented and it is based on the experimental results obtained by measurements on the circuit prototype. We present a solution for automated programming of a commercially available memristor and its implementation in tunable active bandpass filter design. The novelty of this paper is that the active bandpass filter’s central frequency could be programmed during the filter operation, so a pause for memristor state-switching is not required. The experimental results are promising, and open up possibilities for the memristor’s application in analog systems.

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Section: Introductionmentioning

confidence: 99%

The Dynamic Tunability of Memristor-Based Active Filters

Marković,

Potrebić Ivaniš,

Tošić

2023

Micromachines

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“…These features make it provide a novel physical basis for constructing artificial auditory systems ( Gao et al, 2022 ; Zhong et al, 2022 ). Although memristor-based Sallen-Key circuit with tunable gain-bandwidth and center frequency characteristics have been proposed for emulating the cochlea, it still lack experimental demonstration based on memristors’ multi-levels ( Li et al, 2020 ; Barraj et al, 2021 ; Onyejegbu et al, 2022 ). In addition, Wu et al (2021) used the stochastic gradient descent-supervised learning rule to train the preprocessed audio features.…”

Section: Introductionmentioning

confidence: 99%

A bioinspired configurable cochlea based on memristors

et al. 2022

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Cochleas are the basis for biology to process and recognize speech information, emulating which with electronic devices helps us construct high-efficient intelligent voice systems. Memristor provides novel physics for performing neuromorphic engineering beyond complementary metal-oxide-semiconductor technology. This work presents an artificial cochlea based on the shallen-key filter model configured with memristors, in which one filter emulates one channel. We first fabricate a memristor with the TiN/HfOx/TaOx/TiN structure to implement such a cochlea and demonstrate the non-volatile multilevel states through electrical operations. Then, we build the shallen-key filter circuit and experimentally demonstrate the frequency-selection function of cochlea’s five channels, whose central frequency is determined by the memristor’s resistance. To further demonstrate the feasibility of the cochlea for system applications, we use it to extract the speech signal features and then combine it with a convolutional neural network to recognize the Free Spoken Digit Dataset. The recognition accuracy reaches 92% with 64 channels, compatible with the traditional 64 Fourier transform transformation points of mel-frequency cepstral coefficients method with 95% recognition accuracy. This work provides a novel strategy for building cochleas, which has a great potential to conduct configurable, high-parallel, and high-efficient auditory systems for neuromorphic robots.

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Spinel ferrites for resistive random access memory applications

Gayakvad,

Somdatta,

Mathe

et al. 2023

emergent mater.

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Cutting edge science and technology needs high quality data storage devices for their applications in artificial intelligence and digital industries. Resistive random access memory (RRAM) is an emerging nonvolatile memory used for recording and reproducing the digital information. Earlier studies on RRAM applications suggest that spinel ferrite is a potential material. We envisage that the spinel ferrite prepared by a particular route, namely spin coating, will in future optimize the essential parameters for optimal functioning of RRAM. An assertion to our assumptions, few researchers have already obtained important findings for spin coated spinel ferrites. Spin coated spinel ferrites, namely zinc ferrite, nickel ferrite, cobalt ferrite and mixed spinel ferrites, have been investigated for their applications as switching layers in RRAM devices. Particularly, spin coated cobalt ferrite, nickel ferrite and doped nickel ferrite were widely used as resistive switching layers. However, it is noticed that there is a tremendous scope for synthesis and resistive switching characterization of spin coated pure and doped zinc ferrite. Proper doping of special element into spinel ferrite can enhance the resistive switching performance of RRAM devices. Insertion of nano structures and metal layers within switching layer uplifts the performance of spin coated spinel ferrite-based RRAM devices. Active layer in RRAM device synthesized by spin coating technique exhibited good resistive switching properties, namely retention of $$10^{3}$$ 10 3 to $$10^{5}$$ 10 5 s, endurance in the range of $$10^{2}$$ 10 2 to 22,500 cycles and memory window of $$10^{2}$$ 10 2 to $$10^{6}$$ 10 6 . This review article accounts for the optimized parameters obtained especially for the spinel ferrite-based active material synthesized by spin coating justifying the results with appropriate theory. A good co-relation between synthesis parameters and the RRAM functional parameter is separately discussed at the end of review article.

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A variable bandwidth memristor‐based Legendre Optimum low pass filter for radio frequency applications

Cited by 4 publications

References 39 publications

The Dynamic Tunability of Memristor-Based Active Filters

The Dynamic Tunability of Memristor-Based Active Filters

A bioinspired configurable cochlea based on memristors

Spinel ferrites for resistive random access memory applications

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