Is neuromorphic computing disruptive enough to 1) advance our understanding of the brain and 2) make the design and working of (bio)electronic devices efficient and scalable? Article Swipe
Samit Chakrabarty
,
Mihai A. Petrovici
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1017/bel.2023.5
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1017/bel.2023.5
Neuromorphic computing is an approach to computing that is inspired by the structure and function of the brain. In terms of basic research, it aims at improving our understanding of biological intelligence by replicating aspects of its physical substrate – spiking neurons, synaptic plasticity etc. – and harness them towards also replicating its function. With respect to technological advances, it aims to inherit the brain’s combination of computational prowess and extreme energy efficiency; this is thought to foster a plethora of applications, from large-scale neuromorphic systems for machine learning to small-scale edge devices for signal processing and control, for example in the form of wearables for healthcare or adaptive sensors/processors for autonomous agents. The demand and usefulness of neuromorphic computing in bioelectronics is likely to increase in the future as researchers continue to explore its capabilities and develop new applications.
Related Topics
Concepts
Neuromorphic engineering
Scalability
Computer science
Bioelectronics
Wearable computer
Computer architecture
Function (biology)
Scale (ratio)
Wearable technology
Artificial intelligence
Human–computer interaction
Distributed computing
Artificial neural network
Embedded system
Nanotechnology
Biology
Physics
Database
Evolutionary biology
Materials science
Quantum mechanics
Biosensor
Metadata
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- article
- Language
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- Landing Page
- https://doi.org/10.1017/bel.2023.5
- https://www.cambridge.org/core/services/aop-cambridge-core/content/view/019653B3988128A7D22D64E447BC6F8E/S275385242300005Xa.pdf/div-class-title-is-neuromorphic-computing-disruptive-enough-to-1-advance-our-understanding-of-the-brain-and-2-make-the-design-and-working-of-bio-electronic-devices-efficient-and-scalable-div.pdf
- OA Status
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- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4378228129Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1017/bel.2023.5Digital Object Identifier
- Title
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Is neuromorphic computing disruptive enough to 1) advance our understanding of the brain and 2) make the design and working of (bio)electronic devices efficient and scalable?Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-01Full publication date if available
- Authors
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Samit Chakrabarty, Mihai A. PetroviciList of authors in order
- Landing page
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https://doi.org/10.1017/bel.2023.5Publisher landing page
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/019653B3988128A7D22D64E447BC6F8E/S275385242300005Xa.pdf/div-class-title-is-neuromorphic-computing-disruptive-enough-to-1-advance-our-understanding-of-the-brain-and-2-make-the-design-and-working-of-bio-electronic-devices-efficient-and-scalable-div.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/019653B3988128A7D22D64E447BC6F8E/S275385242300005Xa.pdf/div-class-title-is-neuromorphic-computing-disruptive-enough-to-1-advance-our-understanding-of-the-brain-and-2-make-the-design-and-working-of-bio-electronic-devices-efficient-and-scalable-div.pdfDirect OA link when available
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- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| publication_date | 2023-01-01 |
| publication_year | 2023 |
| referenced_works_count | 0 |
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