On-chip tunable Memristor-based flash-ADC converter for artificial intelligence applications
This study presents a novel hybrid memristor (MR)-complementary metal–oxide–semiconductor-based flash analogue-to-digital converter (ADC). The speed and efficiency of the ADC are important aspects that can significantly affect the overall system performance. The flash ADC is considered the fastest t...
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| Vydáno v: | IET circuits, devices & systems Ročník 14; číslo 1; s. 107 - 114 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Stevenage
The Institution of Engineering and Technology
01.01.2020
John Wiley & Sons, Inc |
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| ISSN: | 1751-858X, 1751-8598, 1751-8598 |
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| Abstract | This study presents a novel hybrid memristor (MR)-complementary metal–oxide–semiconductor-based flash analogue-to-digital converter (ADC). The speed and efficiency of the ADC are important aspects that can significantly affect the overall system performance. The flash ADC is considered the fastest type of ADCs; however, its performance is affected by the resistor mismatch. The proposed flash ADC is the first to use tunable MR to replace conventional resistor to generate accurate reference voltages. This is achieved by utilising the highly analogue behaviour observed in multi-state MR devices fabricated and tested by the authors' group. The electrical parameters of the devices have been extracted by device characterisation, then the voltage-threshold adaptive model (VTEAM) has been used to develop a correlated mathematical and Simulation Program with Integrated Circuit Emphasis (SPICE) device model. The proposed MR-based flash-ADC design solves the issue of resistor mismatch that results in encoding errors by the ability to tune the MR resistance value post-processing. Moreover, being a nanoscale component, the usage of MR significantly improves the area efficiency of the target ADC. Furthermore, the proposed design has improved the ADC transfer function characteristic and has lower differential non-linearity and integral non-linearity errors compared with the conventional design. |
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| AbstractList | This study presents a novel hybrid memristor (MR)-complementary metal–oxide–semiconductor-based flash analogue-to-digital converter (ADC). The speed and efficiency of the ADC are important aspects that can significantly affect the overall system performance. The flash ADC is considered the fastest type of ADCs; however, its performance is affected by the resistor mismatch. The proposed flash ADC is the first to use tunable MR to replace conventional resistor to generate accurate reference voltages. This is achieved by utilising the highly analogue behaviour observed in multi-state MR devices fabricated and tested by the authors' group. The electrical parameters of the devices have been extracted by device characterisation, then the voltage-threshold adaptive model (VTEAM) has been used to develop a correlated mathematical and Simulation Program with Integrated Circuit Emphasis (SPICE) device model. The proposed MR-based flash-ADC design solves the issue of resistor mismatch that results in encoding errors by the ability to tune the MR resistance value post-processing. Moreover, being a nanoscale component, the usage of MR significantly improves the area efficiency of the target ADC. Furthermore, the proposed design has improved the ADC transfer function characteristic and has lower differential non-linearity and integral non-linearity errors compared with the conventional design. |
| Author | Abunahla, Heba Mohammad, Baker Azzam, Anas Humood, Khaled |
| Author_xml | – sequence: 1 givenname: Khaled orcidid: 0000-0002-5275-6593 surname: Humood fullname: Humood, Khaled organization: 1System on Chip Center, Electrical and Computer Engineering, Khalifa University (KU), Abu Dhabi, UAE – sequence: 2 givenname: Baker orcidid: 0000-0002-6063-473X surname: Mohammad fullname: Mohammad, Baker email: baker.mohammad@ku.ac.ae organization: 1System on Chip Center, Electrical and Computer Engineering, Khalifa University (KU), Abu Dhabi, UAE – sequence: 3 givenname: Heba surname: Abunahla fullname: Abunahla, Heba organization: 1System on Chip Center, Electrical and Computer Engineering, Khalifa University (KU), Abu Dhabi, UAE – sequence: 4 givenname: Anas surname: Azzam fullname: Azzam, Anas organization: 2System on Chip Center, Mechanical Engineering at KU, Abu Dhabi, UAE |
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| Keywords | memristors analogue behaviour voltage-threshold adaptive model MR resistance value post-processing chip tunable MR-based flash-ADC converter circuit simulation digital signal ADC transfer function characteristic Cadence circuit simulator digital central processing unit analogue-digital conversion electronic engineering computing multistate MR devices artificial intelligence hybrid memristor Simulation Program with Integrated Circuit Emphasis device model integral nonlinearity errors electrical parameters transfer functions flash-ADC design comparators (circuits) flash analogue-to-digital converter |
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| Snippet | This study presents a novel hybrid memristor (MR)-complementary metal–oxide–semiconductor-based flash analogue-to-digital converter (ADC). The speed and... This study presents a novel hybrid memristor (MR)‐complementary metal–oxide–semiconductor‐based flash analogue‐to‐digital converter (ADC). The speed and... |
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| SubjectTerms | ADC transfer function characteristic Analog to digital conversion Analog to digital converters analogue behaviour analogue-digital conversion Artificial intelligence Cadence circuit simulator chip tunable MR-based flash-ADC converter circuit simulation CMOS comparators (circuits) digital central processing unit digital signal Efficiency electrical parameters Electrical properties electronic engineering computing Errors flash analogue-to-digital converter flash-ADC design hybrid memristor integral nonlinearity errors Integrated circuits Internet of Things Linearity Mathematical models Memristors Mismatch (electrical) MR resistance value post-processing multistate MR devices Research Article Resistors Simulation Simulation Program with Integrated Circuit Emphasis device model Transfer functions voltage-threshold adaptive model |
| Title | On-chip tunable Memristor-based flash-ADC converter for artificial intelligence applications |
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