High-Linearity Ta2O5 Memristor and Its Application in Gaussian Convolution Image Denoising.
ACS Appl Mater Interfaces
; 16(36): 47879-47888, 2024 Sep 11.
Article
en En
| MEDLINE
| ID: mdl-39188162
ABSTRACT
In the image Gaussian filtering process, convolving with a Gaussian matrix is essential due to the numerous arithmetic computations involved, predominantly multiplications and additions. This can heavily tax the system's memory, particularly with frequent use. To address this issue, a W/Ta2O5/Ag memristor was employed to substantially mitigate the computational overhead associated with convolution operations. Additionally, an interlayer of ZnO was subsequently introduced into the memristor. The resulting Ta2O5/ZnO heterostructure layer exhibited improved linearity in the pulse response, which enhanced linearity facilitates easy adjustment of the conductance magnitude through a linear mapping of the number of pulses and the conductance. Subsequently, the conductance of the W/Ta2O5/ZnO/Ag bilayer memristor was employed as the weights for the convolution kernel in convolution operations. Gaussian noise removal in image processing was achieved by assembling a 5 × 5 memristor array as the kernel. When denoising was performed using memristor arrays, compared to denoising achieved through Gaussian matrix convolution, an average loss of less than 5% was observed. The provided memristors demonstrate significant potential in convolutional computations, particularly for subsequent applications in convolutional neural networks (CNNs).
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
ACS Appl Mater Interfaces
Asunto de la revista:
BIOTECNOLOGIA
/
ENGENHARIA BIOMEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
China
Pais de publicación:
Estados Unidos