An Inhibitory Neural-Network Circuit Exhibiting Noise Shaping with Subthreshold MOS Neuron Circuits

Utagawa, Akira; Asai, Tetsuya; Hirose, Takahisa; Amemiya, Yoshihito

doi:10.1093/ietfec/e90-a.10.2108

Cited by 10 publications

(7 citation statements)

References 15 publications

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“…Phase synchronization among isolated circuits/PLL (CMOS) [48] Synaptic depression [49] Static Burst signal detection (SET) [50] Noise shaping in inhibitory neural networks [51] Dynamic/static Noise shaping AD conversion (CMOS [52], SET [53]) manufacturing methods, such as those based on molecular self-assembly. Second, regularity also facilitates reuse of logic designs.…”

Section: Cellular Automata Architecturesmentioning

confidence: 99%

Explorations in Morphic Architectures

Asai

Peper

2014

Emerging Nanoelectronic Devices

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Section: Cellular Automata Architecturesmentioning

confidence: 99%

Explorations in Morphic Architectures

Asai

Peper

2014

Emerging Nanoelectronic Devices

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“…CIRCUIT IMPLEMENTATION Fig. 3 shows the model of the proposed circuit, consisting of three neuronal elements, the minimum number of units required to achieve a considerable signal-to-noise ratio ( [12]). The neurons receive the same analog input through excitatory synapses (•) and produce digital pulses toward the global inhibitor Σ [19].…”

Section: Single-electron Integrate and Fire Neuronmentioning

confidence: 99%

“…A number of neuromorphic circuits that operate by utilizing noises and device fabrication mismatches have been proposed. They include neuromorphic CMOS circuits utilizing device fabrication mismatches and environmental noises [12], single-electron circuits employing thermally induced stochastic resonance (SR) (see [13] for details on SR) in signal transmission [14], and single-electron networks performing synchrony detection [15]. This paper explores the possibility of creating novel circuit architectures with single-electron devices, by employing environmental (dynamic) noises, and static noises originating from fabrication mismatches.…”

Section: Introductionmentioning

confidence: 99%

A pulse-density modulation circuit exhibiting noise shaping with single-electron neurons

Kikombo

Asai

Oya

et al. 2009

2009 International Joint Conference on Neural Networks

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Abstract-We propose a bio-inspired circuit performing pulse-density modulation with single-electron devices. The proposed circuit consists of three single-electron neuronal units, receiving the same input and are connected to a common output. The output is inhibitorily fedback to the three neuronal circuits through a capacitive coupling, tuned to obtain a winners-shareall network operation. The circuit performance was evaluated through Monte-Carlo based computer simulations. We demonstrated that the proposed circuit possesses noise-shaping characteristics, where signal and noises are separated into low and high frequency bands respectively. This significantly improved the signal-to-noise ratio (SNR) by 4.34 dB in the coupled network, as compared to the uncoupled one. The noise-shaping properties are as a result of i) the inhibitory feedback between the output and the neuronal circuits, and ii) static noises (originating from device fabrication mismatches) and dynamic noises (as a result of thermally induced random tunneling events) introduced into the network.

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“…On the other hand, many biological systems process information with the help of external or thermal noises, for example, see [2][3][4][5][6][7][8][9][10]. To reproduce this behavior, circuits that exploit noises efficiently, instead of removing them, have been proposed [11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Chaotic Resonance in Forced Chua^|^apos;s Oscillators

Ishimura

Asai

Motomura

2013

Journal of Signal Processing

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Stochastic resonance (SR) is a phenomenon in which dynamic noise is effectively used to induce state transitions in a double-well potential system driven by subthreshold input signals. The noises are supplied to the system as an additional force. Recently, a phenomenon called "chaotic resonance" (CR) has been spotlighted in the literature. CR can be observed in chaotic systems that have multiple strange attractors and the ability to accept subthreshold input signals; i.e., such CR systems do not require any external noise source, unlike traditional SR systems. In this study, we employed Chua's oscillator as a candidate CR system. The oscillator was driven by a sinusoidal voltage source providing subthreshold input signals. In a certain range of input signal frequencies, we observed chaotic state transitions between the two attractors, whereas no state transition between the attractors was observed in the remaining frequency range. These findings indicated that chaotic fluctuations assisted the state transition. Furthermore, we observed nonmonotonic CR characteristics (correlation value and signal-to-noise ratio between the input signal and the output signal) that corresponded to typical nonmonotonic SR curves.

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An Inhibitory Neural-Network Circuit Exhibiting Noise Shaping with Subthreshold MOS Neuron Circuits

Cited by 10 publications

References 15 publications

Explorations in Morphic Architectures

Explorations in Morphic Architectures

A pulse-density modulation circuit exhibiting noise shaping with single-electron neurons

Chaotic Resonance in Forced Chua^|^apos;s Oscillators

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