Delta-sigma modulation in single neurons

Høvin, M.; Wisland, Dag T.; Berg, Y.; Marienborg, J.-T.; Lande, Tor Sverre

doi:10.1109/iscas.2002.1010779

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…the level of analog input is coded into pulse density. Thus a neuron can be considered as a 1-bit A-D converter (Cheung & Taung, 1993;Hovin, 2002) operating in the temporal domain. Figure 1(a) shows a schematic representation of analog-todigital conversion in neurons.…”

Section: A Short Review Of Pulse-density Modulation In Neuronsmentioning

confidence: 99%

A Neuromorphic Single-Electron Circuit for Noise-Shaping Pulse-Density Modulation

Kikombo

Asai

Oya

et al. 2009

International Journal of Nanotechnology and Molecular Computation

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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. 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-tonoise 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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Section: A Short Review Of Pulse-density Modulation In Neuronsmentioning

confidence: 99%

A Neuromorphic Single-Electron Circuit for Noise-Shaping Pulse-Density Modulation

Kikombo

Asai

Oya

et al. 2009

International Journal of Nanotechnology and Molecular Computation

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“…Several efforts have been made to refine the white noise model [25], [26], but most of them still use statistics. In [27] and [28], an equivalence between a modulator and a FM modulator was first identified. Building forth on [27], exact analytical expressions for the output spectrum of a VCO-ADC were calculated in [29].…”

Section: Introductionmentioning

confidence: 99%

A Pulse Frequency Modulation Interpretation of VCOs Enabling VCO-ADC Architectures With Extended Noise Shaping

Gutierrez

Hernández

Cardes

et al. 2018

IEEE Trans. Circuits Syst. I

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In this paper, we propose to study voltage controlled oscillators (VCOs) based on the equivalence with pulse frequency modulators (PFMs). This approach is applied to the analysis of VCO-based analog-to-digital converters (VCO-ADCs) and deviates significantly from the conventional interpretation, where VCO-ADCs have been described as the first-order modulators. A first advantage of our approach is that it unveils systematic error components not described by the equivalence with a conventional modulator. A second advantage is that, by a proper selection of the pulses generated by the PFM, we can theoretically construct an open loop VCO-ADC with an arbitrary noise shaping order. Unfortunately, with the exception of the firstorder noise shaping case, the required pulse waveforms cannot easily be implemented on the circuit level. However, we describe circuit techniques to achieve a good approximation of the required pulse waveforms, which can easily be implemented by practical circuits. Finally, our approach enables a straightforward description of multistage modulator architectures, which is an alternative and practically feasible way to realize a VCO-ADC with extended noise shaping.

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“…This operation is referred to as pulse-density modulation (PDM). A similar operation can be found in spiking neurons [1], e.g., integrate-and-fire neurons (IFNs). The firing rate of the neuron increases as the amount of inputs increases.…”

Section: Introductionmentioning

confidence: 85%

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

Utagawa¹,

Asai²,

Hirose³

et al. 2007

IEICE Transactions on Fundamentals of Electronics, Communicatio

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We designed subthreshold analog MOS circuits implementing an inhibitory network model that performs noise-shaping pulsedensity modulation (PDM) with noisy neural elements, with the aim of developing a possible ultralow-power one-bit analog-to-digital converter. The static and dynamic noises given to the proposed circuits were obtained from device mismatches of current sources (transistors) and externally applied random spike currents, respectively. Through circuit simulations we confirmed that the circuit exhibited noise-shaping properties, and signal-tonoise ratio (SNR) of the network was improved by 7.9 dB compared with that of the uncoupled network as a result of noise shaping.

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Delta-sigma modulation in single neurons

Cited by 5 publications

References 8 publications

A Neuromorphic Single-Electron Circuit for Noise-Shaping Pulse-Density Modulation

A Neuromorphic Single-Electron Circuit for Noise-Shaping Pulse-Density Modulation

A Pulse Frequency Modulation Interpretation of VCOs Enabling VCO-ADC Architectures With Extended Noise Shaping

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

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