Implementation of Encoder/Decoder to Support SNN Model in an IoT Integrated Development Environment based on Neuromorphic Architecture (뉴로모픽 구조 기반 IoT 통합 개발환경에서 SNN 모델을 지원하기 위한 인코더/디코더 구현)

Hoinam Kim (김회남); Yun Young-Sun (윤영선)

doi:10.29056/jsav.2021.12.06

Implementation of Encoder/Decoder to Support SNN Model in an IoT Integrated Development Environment based on Neuromorphic Architecture

Journal of Software Assessment and Valuation
Abbr : JSAV
2021, 17(2), pp.47-57
DOI : 10.29056/jsav.2021.12.06
Publisher : Korea Software Assessment and Valuation Society
Research Area : Engineering > Computer Science
Received : November 12, 2021
Accepted : December 20, 2021
Published : December 31, 2021

Hoinam Kim ¹, Yun Young-Sun ¹

¹한남대학교

Accredited

ABSTRACT

Neuromorphic technology is proposed to complement the shortcomings of existing artificial intelligence technology by mimicking the human brain structure and computational process with hardware. NA-IDE has also been proposed for developing neuromorphic hardware-based IoT applications. To implement an SNN model in NA-IDE, commonly used input data must be transformed for use in the SNN model. In this paper, we implemented a neural coding method encoder component that converts image data into a spike train signal and uses it as an SNN input. The decoder component is implemented to convert the output back to image data when the SNN model generates a spike train signal. If the decoder component uses the same parameters as the encoding process, it can generate static data similar to the original data. It can be used in fields such as image-to-image and speech-to-speech to transform and regenerate input data using the proposed encoder and decoder.

KEYWORDS

Neuromorphic, Spiking Neural Network, Component, NA-IDE, Encoder, Decoder

Citation status

* References for papers published after 2023 are currently being built.

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Journal of Software Assessment and Valuation 2023 KCI Impact Factor : 0.35

Implementation of Encoder/Decoder to Support SNN Model in an IoT Integrated Development Environment based on Neuromorphic Architecture

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Citation status

* References for papers published after 2023 are currently being built.

Journal of Software Assessment and Valuation 2023 KCI Impact Factor : 0.35

Implementation of Encoder/Decoder to Support SNN Model in an IoT Integrated Development Environment based on Neuromorphic Architecture

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KEYWORDS

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* References for papers published after 2023 are currently being built.