Neuromorphic analog communication

Marienborg, J.-T.; Lande, Tor Sverre; Høvin, M.; Abusland, A.

doi:10.1109/icnn.1996.549020

Cited by 6 publications

(3 citation statements)

References 4 publications

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“…Marienborg also developed a processing unit for cochlear implants based on neuromorphic principles [176]. By leveraging nerve-cell modulation in microelectronics and drawing parallels with delta-sigma ADCs, the researchers proposed computationally efficient solutions with reduced power consumption.…”

Section: Hearingmentioning

confidence: 99%

Neuromorphic applications in medicine

et al. 2023

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In recent years, there has been a growing demand for miniaturization, low power consumption, quick treatments, and non-invasive clinical strategies in the healthcare industry. To meet these demands, healthcare professionals are seeking new technological paradigms that can improve diagnostic accuracy while ensuring patient compliance. Neuromorphic engineering, which uses neural models in hardware and software to replicate brain-like behaviors, can help usher in a new era of medicine by delivering low power, low latency, small footprint, and high bandwidth solutions. This paper provides an overview of recent neuromorphic advancements in medicine, including medical imaging and cancer diagnosis, processing of biosignals for diagnosis, and biomedical interfaces, such as motor, cognitive, and perception prostheses. For each section, we provide examples of how brain-inspired models can successfully compete with conventional artificial intelligence algorithms, demonstrating the potential of neuromorphic engineering to meet demands and improve patient outcomes. Lastly, we discuss current struggles in fitting neuromorphic hardware with non-neuromorphic technologies and propose potential solutions for future bottlenecks in hardware compatibility.

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Section: Hearingmentioning

confidence: 99%

Neuromorphic applications in medicine

et al. 2023

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“…To overcome this limitation, some authors proposed more elaborated arbitration techniques with petition aging, i.e. pixels that have been waiting for a long time to transmit information, can be released and continue their normal activity [9]. Unfortunately, the circuitry required in [9] to implement this functionality is more elaborated and the arbitration speed is slow.…”

Section: Introductionmentioning

confidence: 99%

“…pixels that have been waiting for a long time to transmit information, can be released and continue their normal activity [9]. Unfortunately, the circuitry required in [9] to implement this functionality is more elaborated and the arbitration speed is slow. In this paper, we propose simple AER circuitry to implement fast asynchronous communication with aging.…”

Section: Introductionmentioning

confidence: 99%

Pipeline AER arbitration with event aging

Leñero‐Bardallo

Perez-Peña

Carmona-Galán

et al. 2017

2017 IEEE International Symposium on Circuits and Systems (ISCAS)

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We present a simple circuit to handle communication between cells of neuromorphic arrays. It allows cells to operate continuously without waiting for acknowledgement signals back from the AER (Address Event Representation) arbitration circuitry. The module also implements aging of cell petitions i.e., old petitions to access to the AER bus are automatically discarded to give priority to the more recent ones and alleviate the bus congestion. The new arbitration scheme has been implemented and tested. A particular application scenario with an image sensor with spiking pixels that sense light continuously is explained. The sensing errors per event due to discontinued pixel operation can be minimized a factor 8.1. Experimental data obtained with real visual scenes are provided.

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Introduction to Neuromorphic Communication

Lande

The Springer International Series in Engineering and Computer Science

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Neuromorphic analog communication

Cited by 6 publications

References 4 publications

Neuromorphic applications in medicine

Neuromorphic applications in medicine

Pipeline AER arbitration with event aging

Introduction to Neuromorphic Communication

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