Articles | Volume 11, issue 2
https://doi.org/10.5194/jsss-11-233-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/jsss-11-233-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Regular research article
| 
10 Aug 2022
Regular research article |
| 10 Aug 2022
| 10 Aug 2022
Design of a CMOS memristor emulator-based, self-adaptive spiking analog-to-digital data conversion as the lowest level of a self-x hierarchy
Hamam Abd
CORRESPONDING AUTHOR
Lehrstuhl Kognitive Integrierte Sensorsysteme (KISE), Technische Universität Kaiserslautern, Kaiserslautern, Germany
College of Electronics Engineering, Ninevah University, Mosul, Iraq
Andreas König
Lehrstuhl Kognitive Integrierte Sensorsysteme (KISE), Technische Universität Kaiserslautern, Kaiserslautern, Germany
Related authors
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Andreas König
J. Sens. Sens. Syst., 11, 29–40, https://doi.org/10.5194/jsss-11-29-2022, https://doi.org/10.5194/jsss-11-29-2022, 2022
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Bees play a major role in our ecosystem and the human food supply chain. Numerous threats, from pesticides to parasites, endanger bees and possibly cause bee colony collapse. The Varroa mite is one major parasite, and its timely detection and treatment is a key task for beekeepers. Contemporary sensors, electronics, and AI/PR allow vital parameters of bee hives to be monitored. Recent gas sensors (e.g., SGP30 or BME680) allow continuous in-hive parameter and Varroa population monitoring.
Qummar Zaman, Senan Alraho, and Andreas König
J. Sens. Sens. Syst., 10, 193–206, https://doi.org/10.5194/jsss-10-193-2021, https://doi.org/10.5194/jsss-10-193-2021, 2021
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A novel experience replay particle swarm optimization algorithm is presented and successfully deployed to improve the optimization performance for reconfigurable analog integrated circuits of industry 4.0. An optimization approach is introduced that relied on THD-based indirect measurement method that varies from the traditional calibration approach. Instead, the proposed calibration methodology optimizes all characteristics of the reconfigurable amplifier at once.
A. König and K. Thongpull
J. Sens. Sens. Syst., 4, 63–75, https://doi.org/10.5194/jsss-4-63-2015, https://doi.org/10.5194/jsss-4-63-2015, 2015
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A research activity in the context of ambient assisted-living and Internet of Things applications is presented. A new assistance system with an integrated, multi-sensor, low-cost, autonomous, smart spoon device, denoted as Lab-on-Spoon, has been conceived. The goal is to provide assistance for unskilled or challenged consumers by sensory context in ingredients and cooking results.
Successful liquid ingredient recognition and quality assessment, i.e., rotting and contamination, was achieved.
Related subject area
Measurement systems: Sensor signal processing and electronics
Wireless surface acoustic wave resonator sensors: fast Fourier transform, empirical mode decomposition or wavelets for the frequency estimation in one shot?
Ultrasonic measurement setup for monitoring pre-thawing stages of food
Digital twin concepts for linking live sensor data with real-time models
Assisting the automated analysis of chemical–analytical measurements in spirits using validated algorithms and an intuitive user interface
Simulation-based investigation of the metrological interface structural resolution capability of X-ray computed tomography scanners
Smart in-cylinder pressure sensor for closed-loop combustion control
Efficient transient testing procedure using a novel experience replay particle swarm optimizer for THD-based robust design and optimization of self-X sensory electronics in industry 4.0
Intelligent fault detection of electrical assemblies using hierarchical convolutional networks for supporting automatic optical inspection systems
Measurement uncertainty analysis of field-programmable gate-array-based, real-time signal processing for ultrasound flow imaging
Compilation of training datasets for use of convolutional neural networks supporting automatic inspection processes in industry 4.0 based electronic manufacturing
Employing correlation for wireless components and device characterization in reverberation chambers
Impedance model for a high-temperature ceramic humidity sensor
Non-destructive testing of arbitrarily shaped refractive objects with millimetre-wave synthetic aperture radar imaging
Determining the dimension of subsurface defects by active infrared thermography – experimental research
Inverse calculation of strain profiles from ETDR measurements using artificial neural networks
An ultra-low noise capacitance to voltage converter for sensor applications in 0.35 µm CMOS
Development of a non-contact torque transducer based on the laser speckle contrast method
Development of a chopper charge amplifier for measuring the cavity pressure inside injection moulding tools and signal optimisation with a Kalman filter
Optimized mixed-domain signal synthesis for broadband impedance spectroscopy measurements on lithium ion cells for automotive applications
High-accuracy current measurement with low-cost shunts by means of dynamic error correction
A compact readout platform for spectral-optical sensors
High-speed camera-based measurement system for aeroacoustic investigations
Shutter-less calibration of uncooled infrared cameras
A novel approach for detecting HMDSO poisoning of metal oxide gas sensors and improving their stability by temperature cycled operation
Micro- and nanocoordinate measurements of micro-parts with 3-D tunnelling current probing
An electrical characterisation system for the real-time acquisition of multiple independent sensing parameters from organic thin film transistors
Piezoelectric transceiver matching for multiple frequencies
Metal oxide semiconductor gas sensor self-test using Fourier-based impedance spectroscopy
Work area monitoring in dynamic environments using multiple auto-aligning 3-D sensors
Principal component analysis for fast and automated thermographic inspection of internal structures in sandwich parts
Near-field interrogation of SAW resonators on rotating machinery
Magnetic properties of CHAMP and their effects on in-orbit calibration
Angel Scipioni, Pascal Rischette, and Agnès Santori
J. Sens. Sens. Syst., 12, 247–260, https://doi.org/10.5194/jsss-12-247-2023, https://doi.org/10.5194/jsss-12-247-2023, 2023
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Many applications which measure physical quantities rely on wireless surface acoustic wave sensors. The accuracy of this sensor depends directly on the measurement of its main frequency. This paper aims to compare three methods for this measurement in one shot: fast Fourier transform, discrete wavelet transform, and empirical mode decomposition. Results show that the choice of the method is conditioned by the disturbance level and that the wavelet method is the best way for harsh environments.
Ruchi Jha, Walter Lang, and Reiner Jedermann
J. Sens. Sens. Syst., 12, 133–139, https://doi.org/10.5194/jsss-12-133-2023, https://doi.org/10.5194/jsss-12-133-2023, 2023
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In order to save time and avoid overheating of food during unfreezing, the study of ice content can be very useful. The aim of the research is to design an ultrasound-based sensor system that is able to comment on the content of ice in the sample food product. Some sample food products are tested, and the observations and challenges concerning the same are mentioned in the research paper.
Reiner Jedermann, Kunal Singh, Walter Lang, and Pramod Mahajan
J. Sens. Sens. Syst., 12, 111–121, https://doi.org/10.5194/jsss-12-111-2023, https://doi.org/10.5194/jsss-12-111-2023, 2023
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Mathematical models are often required to process sensor data in a digital twin platform. The translation of models to an updateable format enables predicting hidden states of the physical object, which are not directly measurable. The linking of different models is demonstrated by data from field tests on fruit transportation in refrigerated containers. We programmed a streaming platform that enables easy integration of such updatable models with only a few milliseconds of processing overhead.
Andreas T. Grasskamp, Satnam Singh, Helen Haug, and Tilman Sauerwald
J. Sens. Sens. Syst., 12, 93–101, https://doi.org/10.5194/jsss-12-93-2023, https://doi.org/10.5194/jsss-12-93-2023, 2023
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In this work, we have developed and validated a semi-automatic approach that greatly reduces the amount of interaction and effort needed for analyzing samples via gas chromatography–mass spectrometry. Further, unlike many other approaches, our developed tool is accessible to the novice and does not require any programming experience. Using whisky as an example substance, we show how the analysis method compares to conventional software, and we validate our approach against that.
Matthias Busch and Tino Hausotte
J. Sens. Sens. Syst., 12, 1–8, https://doi.org/10.5194/jsss-12-1-2023, https://doi.org/10.5194/jsss-12-1-2023, 2023
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The paper presents a specimen and evaluation method for interface structural resolution testing of X-ray computed tomography systems based on CT simulations. The geometry is oriented to the norms of image quality investigation. The evaluation is based on profile lines of the cross-sectional images that pass through the boreholes. All statements on resolution refer to the entire measurement chain and, thus, in addition to the reconstruction algorithm also to the surface determination method used.
Dennis Vollberg, Peter Gibson, Günter Schultes, Hans-Werner Groh, and Thomas Heinze
J. Sens. Sens. Syst., 11, 1–13, https://doi.org/10.5194/jsss-11-1-2022, https://doi.org/10.5194/jsss-11-1-2022, 2022
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We developed a smart in-cylinder pressure sensor for closed-loop combustion control. The sensor concept is based on a robust and reliable steel membrane equipped with highly strain-sensitive and temperature-stable thin films. The sensor system is complemented by a smart electronics allowing real-time data processing for calculation of different combustion parameters. The data are utilized to control the igniting timing of a spark plug for efficient operation of a combustion engine.
Qummar Zaman, Senan Alraho, and Andreas König
J. Sens. Sens. Syst., 10, 193–206, https://doi.org/10.5194/jsss-10-193-2021, https://doi.org/10.5194/jsss-10-193-2021, 2021
Short summary
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A novel experience replay particle swarm optimization algorithm is presented and successfully deployed to improve the optimization performance for reconfigurable analog integrated circuits of industry 4.0. An optimization approach is introduced that relied on THD-based indirect measurement method that varies from the traditional calibration approach. Instead, the proposed calibration methodology optimizes all characteristics of the reconfigurable amplifier at once.
Alida Ilse Maria Schwebig and Rainer Tutsch
J. Sens. Sens. Syst., 9, 363–374, https://doi.org/10.5194/jsss-9-363-2020, https://doi.org/10.5194/jsss-9-363-2020, 2020
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In order to further increase the performance of neural networks in the field of optical quality assurance of soldered joints, a hierarchical classifier can be used instead of a single network. The global expansion of the classifier enables the inspection task to be distributed over several subnetworks, which results in higher accuracy. Since the individual sub-models only concentrate on the identification of certain characteristics, categorical problems can be solved more effectively.
Richard Nauber, Lars Büttner, and Jürgen Czarske
J. Sens. Sens. Syst., 9, 227–238, https://doi.org/10.5194/jsss-9-227-2020, https://doi.org/10.5194/jsss-9-227-2020, 2020
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To improve the energy efficiency of industrial processes, such as continuous steel casting, lab-scale experiments with liquid metals are performed. We present an ultrasound Doppler signal process for multiplane, high-frame-rate flow imaging. We achieve real-time operations with an efficient implementation in a field-programmable gate array (FPGA). We analyze the contributions to the uncertainty of the velocity measurement and relate it to its fundamental limit.
Alida Ilse Maria Schwebig and Rainer Tutsch
J. Sens. Sens. Syst., 9, 167–178, https://doi.org/10.5194/jsss-9-167-2020, https://doi.org/10.5194/jsss-9-167-2020, 2020
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This article presents a classification concept based on deep learning as an additional optical test method for real-time visualization and analysis of electrical assemblies in the production environment. For this purpose, a neural convolutional network is used to identify the quality of the solder joint of surface-mounted chip components in the inspection images. The concept can be used to increase the detection performance of the solder joint inspection systems.
Christoph Cammin, Dmytro Krush, Ralf Heynicke, and Gerd Scholl
J. Sens. Sens. Syst., 8, 185–194, https://doi.org/10.5194/jsss-8-185-2019, https://doi.org/10.5194/jsss-8-185-2019, 2019
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Reverberation chambers are well-proven test environments for RF measurements. Typically, mean values are taken from the measurements to characterize the equipment under test. In the novel approach presented in this paper, the correlation of measured sample sequences is utilized to detect deviations, in particular of the radiation characteristics, from reference equipment.
Henrik Lensch, Manuel Bastuck, Tobias Baur, Andreas Schütze, and Tilman Sauerwald
J. Sens. Sens. Syst., 8, 161–169, https://doi.org/10.5194/jsss-8-161-2019, https://doi.org/10.5194/jsss-8-161-2019, 2019
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The measurement of humidity in industrial applications is still an important research issue. Especially under rough operation conditions the current humidity sensor comes to its limitations. To this end, we are developing an integrated sensor system using a metal oxide sensor with impedance spectroscopy as multi-signal generation allowing the discrimination of humidity and reducing gases. The submitted paper focuses on the modeling of the humidity-dependent aspects of impedance.
Ingrid Ullmann, Julian Adametz, Daniel Oppelt, Andreas Benedikter, and Martin Vossiek
J. Sens. Sens. Syst., 7, 309–317, https://doi.org/10.5194/jsss-7-309-2018, https://doi.org/10.5194/jsss-7-309-2018, 2018
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Millimetre-wave radar is an emerging technique for non-destructive testing: it is less costly than X-rays and has no ionizing radiation. Compared to ultrasound it does not require the device under test to be immersed in water. This article presents methods for high-resolution millimetre-wave radar imaging without a priori knowledge of the object's shape. A polymer device with simulated material defects is examined, which could be depicted precisely.
Slawomir Grys
J. Sens. Sens. Syst., 7, 153–160, https://doi.org/10.5194/jsss-7-153-2018, https://doi.org/10.5194/jsss-7-153-2018, 2018
Robin Höhne, Pawel Kostka, and Niels Modler
J. Sens. Sens. Syst., 6, 389–394, https://doi.org/10.5194/jsss-6-389-2017, https://doi.org/10.5194/jsss-6-389-2017, 2017
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This paper focuses on a novel carbon fibre sensor technology that exploits the low-cost and low-energy electrical reflectometry method for a spatially resolved strain measurement. The application of artificial neural networks for mapping the measured electrical signal to the existing strain profile is demonstrated. The potential and current limits are highlighted. The sensor is a promising part for the next generation of light-weight structures with operando health monitoring systems.
Alexander Utz, Christian Walk, Norbert Haas, Tatjana Fedtschenko, Alexander Stanitzki, Mir Mokhtari, Michael Görtz, Michael Kraft, and Rainer Kokozinski
J. Sens. Sens. Syst., 6, 285–301, https://doi.org/10.5194/jsss-6-285-2017, https://doi.org/10.5194/jsss-6-285-2017, 2017
Alberto Garinei and Roberto Marsili
J. Sens. Sens. Syst., 6, 253–258, https://doi.org/10.5194/jsss-6-253-2017, https://doi.org/10.5194/jsss-6-253-2017, 2017
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When a torque measurement is required, torque transducers show many drawbacks during their use: the usual limits are the need for contact and the effects on shaft line parameters. A new approach is proposed in this work: a non-contact torque meter for a machine shaft has been developed, based on a laser speckle contrast method. It carries out torque measurements evaluating the torsional displacement between two distinct sections of the shaft, through the monitoring of their roughness.
Manuel Schneider, Alexander Jahn, Norbert Greifzu, and Norbert Fränzel
J. Sens. Sens. Syst., 6, 199–210, https://doi.org/10.5194/jsss-6-199-2017, https://doi.org/10.5194/jsss-6-199-2017, 2017
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This article describes a chopper amplifier which has been specially developed for piezoelectric pressure sensors. It is shown that the amplifier provides good results for pressure measurement in injection moulds. A special feature of this work is the signal optimisation through the use of a Kalman filter.
Peter Haußmann and Joachim Melbert
J. Sens. Sens. Syst., 6, 65–76, https://doi.org/10.5194/jsss-6-65-2017, https://doi.org/10.5194/jsss-6-65-2017, 2017
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A method to generate broadband waveforms with low peak-to-peak amplitude based on distinct frequency domain profiles is presented, which includes random phase variation and numerical optimization. The peak-to-peak amplitude can be reduced by 71 % compared to zero-phase pulses with equal frequency domain characteristics. Used as excitation signals for impedance spectroscopy, the waveforms yield good results at significantly reduced measurement duration compared to established measurement methods.
Patrick Weßkamp and Joachim Melbert
J. Sens. Sens. Syst., 5, 389–400, https://doi.org/10.5194/jsss-5-389-2016, https://doi.org/10.5194/jsss-5-389-2016, 2016
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Measurement of electrical current is important for many scientific and industrial applications. Often shunt resistors are used. However, thermal effects due to self-heating and ambient temperature variation limit the achievable accuracy.
In this work, a dynamic compensation method is presented which takes static and dynamic temperature drift effects into account. It significantly reduces the remaining measurement errors. The approach can also be used to improve existing measurement systems.
Roland Wuchrer, Sabrina Amrehn, Luhao Liu, Thorsten Wagner, and Thomas Härtling
J. Sens. Sens. Syst., 5, 157–163, https://doi.org/10.5194/jsss-5-157-2016, https://doi.org/10.5194/jsss-5-157-2016, 2016
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The continuous monitoring of industrial and environmental processes is becoming an increasingly important aspect with both economic and societal impact. To realize this task, spectral-optical sensors with their outstanding properties in terms of sensitivity and reliability are a potential solution. However, for exploiting these sensors in a cost- and energy-efficient sensing system, a miniaturized readout unit is needed. Here we present a card-size, inexpensive, and robust readout electronics.
Johannes Gürtler, Daniel Haufe, Anita Schulz, Friedrich Bake, Lars Enghardt, Jürgen Czarske, and Andreas Fischer
J. Sens. Sens. Syst., 5, 125–136, https://doi.org/10.5194/jsss-5-125-2016, https://doi.org/10.5194/jsss-5-125-2016, 2016
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The interaction of sound and flow enables an efficient noise damping. Understanding this aeroacoustic damping phenomenon requires simultaneous measurement of flow and sound fields. Using a high-speed CMOS camera, two-component flow velocity measurements are performed in a three-dimensional region of interest. The sensor system can simultaneously capture sound and turbulent flow velocity oscillations. The presented measurements reveal that the sound energy is transferred into flow energy.
A. Tempelhahn, H. Budzier, V. Krause, and G. Gerlach
J. Sens. Sens. Syst., 5, 9–16, https://doi.org/10.5194/jsss-5-9-2016, https://doi.org/10.5194/jsss-5-9-2016, 2016
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Infrared cameras based on microbolometer focal plane arrays (FPAs) are the most widely used cameras in thermography. For acceptable measurement uncertainty values, the disturbing influences of changing ambient temperature have to be considered. We propose a TEC-less and shutter-less correction approach based on additional temperature measurements inside the IR camera. The effects on the pixel responsivity and offset voltage are considered separately.
M. Schüler, T. Sauerwald, and A. Schütze
J. Sens. Sens. Syst., 4, 305–311, https://doi.org/10.5194/jsss-4-305-2015, https://doi.org/10.5194/jsss-4-305-2015, 2015
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We study the effect of HMDSO vapor on an SnO2-based gas sensor in temperature cycled operation (TCO). The poisoning can be quantified at early stages with a resolution of ±85 ppm*min using TCO. This approach provides a simple method for early detection of HMDSO poisoning.
The stability of gas discrimination by linear discriminant analysis (LDA) can be improved using normalization, which in turn facilitates a more accurate determination of the poisoning state by hierarchical LDA discrimination.
A. Schuler, T. Hausotte, and Z. Sun
J. Sens. Sens. Syst., 4, 199–208, https://doi.org/10.5194/jsss-4-199-2015, https://doi.org/10.5194/jsss-4-199-2015, 2015
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Measurement tasks of modern micro- and nanometrology with decreasing structure sizes and rising aspect ratios require nanometre-resolving 3-D capable sensors. A 3-D probing system based on electrical interaction is presented which is operated on a nanopositioning system NMM-1. New 3-D measurement procedures for the probing system as well as for micrometrology measurement tasks in general are shown.
A. Dragoneas, L. Hague, and M. Grell
J. Sens. Sens. Syst., 4, 169–177, https://doi.org/10.5194/jsss-4-169-2015, https://doi.org/10.5194/jsss-4-169-2015, 2015
A. Ens and L. M. Reindl
J. Sens. Sens. Syst., 4, 9–16, https://doi.org/10.5194/jsss-4-9-2015, https://doi.org/10.5194/jsss-4-9-2015, 2015
M. Schüler, T. Sauerwald, and A. Schütze
J. Sens. Sens. Syst., 3, 213–221, https://doi.org/10.5194/jsss-3-213-2014, https://doi.org/10.5194/jsss-3-213-2014, 2014
Y. Wang, D. Ewert, T. Meisen, D. Schilberg, and S. Jeschke
J. Sens. Sens. Syst., 3, 113–120, https://doi.org/10.5194/jsss-3-113-2014, https://doi.org/10.5194/jsss-3-113-2014, 2014
D. Griefahn, J. Wollnack, and W. Hintze
J. Sens. Sens. Syst., 3, 105–111, https://doi.org/10.5194/jsss-3-105-2014, https://doi.org/10.5194/jsss-3-105-2014, 2014
J.-M. Boccard, P. Katus, R. Renevier, L. M. Reindl, and J.-M. Friedt
J. Sens. Sens. Syst., 2, 147–156, https://doi.org/10.5194/jsss-2-147-2013, https://doi.org/10.5194/jsss-2-147-2013, 2013
H. Lühr, F. Yin, and R. Bock
J. Sens. Sens. Syst., 2, 9–17, https://doi.org/10.5194/jsss-2-9-2013, https://doi.org/10.5194/jsss-2-9-2013, 2013
Cited articles
Aamir, S. A., Stradmann, Y., Müller, P., Pehle, C., Hartel, A., Grübl, A., Schemmel, J., and Meier, K.: An accelerated lif neuronal network array for a large-scale mixed-signal neuromorphic architecture, IEEE T. Circuit. Syst. I, 65, 4299–4312, 2018. a
Abd, H. and König, A.: A Compact Four Transistor CMOS-Design of a Floating Memristor for Adaptive Spiking Neural Networks and Corresponding Self-X Sensor Electronics to Industry 4.0, tm-Technisches Messen, 87, s91–s96, 2020. a
Abd, H. and König, A.: Adaptive Spiking Sensor System Based on CMOS
Memristors Emulating Long and Short-Term Plasticity of Biological Synapses
for Industry 4.0 Applications, tm-Technisches Messen, 88, s114–s119,
2021a. a
Abd, H. and König, A.: D10.3 Adaptive Spiking Sensor Electronics Inspired
by Biological Nervous System Based on Memristor Emulator for Industry 4.0
Applications, SMSI 2021-Sensors and Instrumentation, 232–233, https://doi.org/10.5162/SMSI2021/D10.3, 2021b. a
Burr, G. W., Shelby, R. M., Sebastian, A., Kim, S., Kim, S., Sidler, S., Virwani, K., Ishii, M., Narayanan, P., Fumarola, A., Sanches, L. L., Boybat, I., Gallo, M. L., Moon, K., Woo, J., Hwang, H., and Leblebici, Y.: Neuromorphic computing using non-volatile memory, Adv. Phys. X, 2, 89–124, 2017. a
Carr, C. and Konishi, M.: A circuit for detection of interaural time
differences in the brain stem of the barn owl, J. Neurosci., 10, 3227–3246, 1990. a
Carr, C. E. and Christensen-Dalsgaard, J.: Sound localization strategies in
three predators, Brain. Behav. Evol., 86, 17–27, 2015. a
Carr, C. E. and Konishi, M.: Axonal delay lines for time measurement in the
owl's brainstem, P. Natl. Acad. Sci. USA, 85, 8311–8315, 1988. a
Covi, E., Lin, Y.-H., Wang, W., Stecconi, T., Milo, V., Bricalli, A., Ambrosi, E., Pedretti, G., Tseng, T.-Y., and Ielmini, D.: A volatile RRAM synapse for neuromorphic computing, in: 2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 27 November 2019, Genoa, Italy, 903–906, https://doi.org/10.1109/ICECS46596.2019.8965044, 2019. a
Doge, J., Schonfelder, G., Streil, G. T., and Konig, A.: An HDR CMOS image
sensor with spiking pixels, pixel-level ADC, and linear characteristics, IEEE
T. Circuit. Syst. II, 49, 155–158, 2002. a
Graves, C. E., Li, C., Sheng, X., Miller, D., Ignowski, J., Kiyama, L., and
Strachan, J. P.: In-Memory Computing with Memristor Content Addressable
Memories for Pattern Matching, Adv. Mater., 32, 2003437, https://doi.org/10.1002/adma.202003437, 2020. a, b
Grothe, B., Pecka, M., and McAlpine, D.: Mechanisms of sound localization in
mammals, Physiol. Rev., 90, 983–1012, 2010. a
Guo, W., Fouda, M. E., Eltawil, A. M., and Salama, K. N.: Neural coding in
spiking neural networks: A comparative study for robust neuromorphic systems,
Front. Neurosci., 15, 212, https://doi.org/10.3389/fnins.2021.638474, 2021. a
Henzler, S.: Time-to-digital converter basics, in: Time-to-digital converters, Springer, 5–18, https://doi.org/10.1007/978-90-481-8628-0_2, 2010a. a, b
Henzler, S.: Theory of tdc operation, in: Time-to-digital Converters, Springer, 19–42, https://doi.org/10.1007/978-90-481-8628-0_3, 2010b. a, b
Indiveri, G.: A low-power adaptive integrate-and-fire neuron circuit, in:
vol. 4, Proceedings of the 2003 International Symposium on Circuits and Systems, ISCAS'03, 25–28 May 2003, Bangkok, Thailand
https://doi.org/10.1109/ISCAS.2003.1206342, 2003. a
Jeffress, L. A.: A place theory of sound localization, J. Compar. Physiol. Psychol., 41, 35, https://doi.org/10.1037/h0061495, 1948. a, b, c, d
Jo, S.-H., Cho, H.-W., and Yoo, H.-J.: A fully reconfigurable universal sensor analog front-end IC for the internet of things era, IEEE Sensors J., 19, 2621–2633, 2019. a
Kammara, A. C. and König, A.: P5-Increasing the Resolution of an Integrated Adaptive Spike Coded Sensor to Digital Conversion Neuro-Circuit by an Enhanced Place Coding Layer, Tagungsband, SMSI – Sensor and Measurement Science International, 157–166, https://doi.org/10.5162/AHMT2014/P5, 2014b. a, b
Kandel, E. R.: From nerve cells to cognition: The internal cellular
representation required for perception and action, Princip. Neural Sci., 4, 381–403, 2000. a
Kim, M.-K. and Lee, J.-S.: Short-term plasticity and long-term potentiation in artificial biosynapses with diffusive dynamics, ACS Nano, 12, 1680–1687,
2018a. a
Kim, M.-K. and Lee, J.-S.: Short-term plasticity and long-term potentiation in artificial biosynapses with diffusive dynamics, ACS Nano, 12, 1680–1687,
2018b. a
Kim, S., Du, C., Sheridan, P., Ma, W., Choi, S., and Lu, W. D.: Experimental
demonstration of a second-order memristor and its ability to biorealistically
implement synaptic plasticity, Nano Lett., 15, 2203–2211, 2015. a
Kim, S. G., Han, J. S., Kim, H., Kim, S. Y., and Jang, H. W.: Recent advances
in memristive materials for artificial synapses, Adv. Mater Technol., 3, 1800457, https://doi.org/10.1002/admt.201800457, 2018. a
Kim, T., Hu, S., Kim, J., Kwak, J. Y., Park, J., Lee, S., Kim, I., Park, J.-K., and Jeong, Y.: Spiking Neural Network (SNN) with memristor synapses having non-linear weight update, Front. Comput. Neurosci., 15, 22, https://doi.org/10.3389/fncom.2021.646125, 2021. a
König, A. and Kammara, A. C.: B2. 1-Robust & Technology Agnostic
Integrated Implementation of Future Sensory Electronics based on Spiking
Information Processing for Industry 4.0, in: Proceedings Sensor 2017, 30 May–1 June 2017, Nuremberg, Germany, 177–182, https://doi.org/10.5162/sensor2017/B2.1, 2017. a, b
Lee, S., Shi, C., Wang, J., Sanabria, A., Osman, H., Hu, J., and
Sánchez-Sinencio, E.: A built-in self-test and in situ analog circuit
optimization platform, IEEE T. Circuit. Syst. I, 65, 3445–3458, 2018a. a
Lee, S., Shi, C., Wang, J., Sanabria, A., Osman, H., Hu, J., and
Sánchez-Sinencio, E.: A built-in self-test and in situ analog circuit
optimization platform, IEEE T. Circuit. Syst. I, 65, 3445–3458, 2018b. a
Leitch, O., Anderson, A., Kirkbride, K. P., and Lennard, C.: Biological
organisms as volatile compound detectors: A review, Forensic Sci. Int., 232, 92–103, 2013. a
Li, J., Dong, Z., Luo, L., Duan, S., and Wang, L.: A novel versatile window
function for memristor model with application in spiking neural network,
Neurocomputing, 405, 239–246, 2020. a
Li, S., Zeng, F., Chen, C., Liu, H., Tang, G., Gao, S., Song, C., Lin, Y., Pan, F., and Guo, D.: Synaptic plasticity and learning behaviours mimicked through Ag interface movement in an Ag/conducting polymer/Ta memristive system, J. Mater. Chem. C, 1, 5292–5298, 2013. a
Lin, Y.-B., Lin, Y.-W., Lin, J.-Y., and Hung, H.-N.: SensorTalk: An IoT device failure detection and calibration mechanism for smart farming, Sensors, 19, 4788, https://doi.org/10.3390/s19214788, 2019. a
Lu, Y., Yuan, G., Der, L., Ki, W.-H., and Yue, C. P.: A ±0.5 % Precision On-Chip Frequency Reference With Programmable Switch Array for Crystal-Less Applications, IEEE T. Circuit. Syst. II, 60, 642–646, 2013. a
Lv, Z., Zhou, Y., Han, S.-T., and Roy, V.: From biomaterial-based data storage to bio-inspired artificial synapse, Mater. Today, 21, 537–552, 2018. a
Mannan, Z. I., Kim, H., and Chua, L.: Implementation of Neuro-Memristive
Synapse for Long-and Short-Term Bio-Synaptic Plasticity, Sensors, 21, 644, https://doi.org/10.3390/s21020644, 2021. a
Manouras, V., Stathopoulos, S., Serb, A., and Prodromakis, T.: Technology
agnostic frequency characterization methodology for memristors, Scient. Rep., 11, 1–11, 2021. a
Martin, S. J., Grimwood, P. D., and Morris, R. G.: Synaptic plasticity and
memory: an evaluation of the hypothesis, Annu. Rev. Neurosci., 23, 649–711, 2000. a
Mehonic, A., Sebastian, A., Rajendran, B., Simeone, O., Vasilaki, E., and
Kenyon, A. J.: Memristors – From In-Memory Computing, Deep Learning
Acceleration, and Spiking Neural Networks to the Future of Neuromorphic and
Bio-Inspired Computing, Adv. Intell. Syst., 2, 2000085, https://doi.org/10.1002/aisy.202000085, 2020. a
Meijer, G.: Smart sensor systems, John Wiley & Sons, ISBN 978-0-470-86691-7, 2008. a
Midya, R., Wang, Z., Asapu, S., Joshi, S., Li, Y., Zhuo, Y., Song, W., Jiang, H., Upadhay, N., Rao, M., Lin, P., Li, C., Xia, Q., and Yang, J. J.: Artificial neural network (ANN) to spiking neural network (SNN) converters based on diffusive memristors, Adv. Electron. Mater., 5, 1900060, https://doi.org/10.1002/aelm.201900060, 2019. a
Ohno, T., Hasegawa, T., Tsuruoka, T., Terabe, K., Gimzewski, J. K., and Aono,
M.: Short-term plasticity and long-term potentiation mimicked in single
inorganic synapses, Nat. Mater., 10, 591–595, 2011. a
Park, Y., Kim, M.-K., and Lee, J.-S.: Emerging memory devices for artificial
synapses, J. Mater. Chem. C, 8, 9163–9183, 2020. a
Ren, Y., Hu, L., Mao, J.-Y., Yuan, J., Zeng, Y.-J., Ruan, S., Yang, J.-Q.,
Zhou, L., Zhou, Y., and Han, S.-T.: Phosphorene nano-heterostructure based
memristors with broadband response synaptic plasticity, J. Mater. Chem. C, 6, 9383–9393, 2018. a
Seidl, A. H., Rubel, E. W., and Harris, D. M.: Mechanisms for adjusting
interaural time differences to achieve binaural coincidence detection, J. Neurosci., 30, 70–80, 2010. a
Shchanikov, S., Zuev, A., Bordanov, I., Danilin, S., Lukoyanov, V., Korolev, D., Belov, A., Pigareva, Y., Gladkov, A., Pimashkin, A., Mikhaylov, A., Kazantsev, V., and Serb, A.: Designing a bidirectional, adaptive neural interface incorporating machine learning capabilities and memristor-enhanced hardware, Chaos Solit. Fract., 142, 110504, https://doi.org/10.1016/j.chaos.2020.110504, 2021. a, b
Staszewski, R. B., Wallberg, J. L., Rezeq, S., Hung, C.-M., Eliezer, O. E., Vemulapalli, S. K., Fernando, C., Maggio, K., Staszewski, R., Barton, N., Lee, M. C., Cruise, P., Entezari, M., Muhammad, K., and Leipold, D.: All-digital PLL and transmitter for mobile phones, IEEE J. Solid-State Circuit., 40, 2469–2482, 2005. a, b
Stieve, H.: Sensors of biological organisms–biological transducers, Sensors
Actuat., 4, 689–704, 1983. a
Subramanyam, K. and Chandra, A.: Conception and First Implementation of Novel
Sensory Signal Conditioning and Digital Conversion Electronics Based on
Spiking Neuron Ensembles for Inherently Robust Processing in Aggressively
Scaled Integration Technologies, Technische Universität Kaiserslautern,
Kaiserslautern, https://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/4774
(last access: 4 August 2022), 2017. a, b
Tavolga, W. N., Popper, A. N., and Fay, R. R.: Hearing and sound communication in fishes, Springer Science & Business Media, https://doi.org/10.1007/978-1-4615-7186-5, 2012. a
Technology Xfab: Technology X-FAB, https://www.xfab.com/technology, last access: 4 August 2022. a
Thorpe, S. and Gautrais, J.: Rank order coding, in: Computational neuroscience, Springer, 113–118, https://doi.org/10.1007/978-1-4615-4831-7_19, 1998. a
Thorpe, S., Delorme, A., and Van Rullen, R.: Spike-based strategies for rapid
processing, Neural Netw., 14, 715–725, 2001. a
Von Neumann, J.: First Draft of a Report on the EDVAC, Moore School of Electrical Engineering, Univ. of Pennsylvania, Philadelphia, http://abelgo.cn/cs101/papers/Neumann.pdf (last access: 9 August 2022), 30 June 1945. a
Wang, Z., Joshi, S., Savel'ev, S. E., Jiang, H., Midya, R., Lin, P., Hu, M., Ge, N., Strachan, J. P., Li, Z., Wu, Q., Barnell, M., Li, G. L., Xin, H. L., Williams, R. S., Xia, Q., and Yang J. J.: Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing, Nat. Mater., 16, 101–108, 2017. a
Werthschützky, R.: Sensor Technologien 2022, AMA Verband für Sensorik
und Messtechnik eV, https://www.konstruktionspraxis.vogel.de/ama-verband-veroeffentlicht-studie-sensor-technologien-2022 (last access: 4 August 2022), 2018. a
Wu, L., Liu, H., Lin, J., and Wang, S.: Volatile and Nonvolatile Memory
Operations Implemented in a Pt/HfO2/Ti Memristor, IEEE T. Elect. Devic., 68, 1622–1626, 2021.
a
Yang, M., Zhao, X., Tang, Q., Cui, N., Wang, Z., Tong, Y., and Liu, Y.:
Stretchable and conformable synapse memristors for wearable and implantable
electronics, Nanoscale, 10, 18135–18144, 2018. a
Yang, Y., Yin, M., Yu, Z., Wang, Z., Zhang, T., Cai, Y., Lu, W. D., and Huang, R.: Multifunctional Nanoionic Devices Enabling Simultaneous Heterosynaptic Plasticity and Efficient In-Memory Boolean Logic, Adv. Elect.
Mater., 3, 1700032, https://doi.org/10.1002/aelm.201700032, 2017. a
Zaman, Q., Alraho, S., and König, A.: Efficient transient testing procedure using a novel experience replay particle swarm optimizer for THD-based robust design and optimization of self-X sensory electronics in industry 4.0, J. Sens. Sens. Syst., 10, 193–206, https://doi.org/10.5194/jsss-10-193-2021, 2021. a
Zhang, X., Liu, S., Zhao, X., Wu, F., Wu, Q., Wang, W., Cao, R., Fang, Y., Lv, H., Long, S., Liu, Q., and Liu, M.: Emulating short-term and long-term plasticity of bio-synapse based on Cu/a-Si/Pt memristor, IEEE Elect. Devic. Lett., 38, 1208–1211, 2017. a
Zhang, Y., Wang, Z., Zhu, J., Yang, Y., Rao, M., Song, W., Zhuo, Y., Zhang, X., Cui, M., Shen, L., Huang, R., and Yang, J.: Brain-inspired computing with memristors: Challenges in devices, circuits, and systems, Appl. Phys. Rev., 7, 011308, https://doi.org/10.1063/1.5124027, 2020. a, b
Short summary
We pursue a promising novel self-adaptive spiking neural analog-to-digital data conversion (SN-ADC) design that uses spike time to carry information. Thus, SN-ADC can be effectively translated to aggressive new technologies to implement reliable advanced sensory electronic systems. The SN-ADC supports self-x (self-calibration, self-optimization, and self-healing) and machine learning required for the internet of things and Industry 4.0 and is based on a self-adaptive CMOS memristor.
We pursue a promising novel self-adaptive spiking neural analog-to-digital data conversion...
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