Presentation 2009-03-10
A Hardware Implementable Model of Sigma-Delta Cellular Neural Network
Hisashi AOMORI, Yuki NAITO, Mamoru TANAKA,
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Abstract(in English) The sigma-delta cellular neural network (SD-CNN) is a complete framework of a spatial domain sigma-delta modulator, and has a very high image reconstruction (AD-to-DA) performance. In this architecture, the A-template given by a 2-D low pass filter (LPF) is used for a digital to analogue converter (DAC), the C-template works as an integrator, and the nonlinear output function is for the bilevel output. By exploiting to the nonlinear optimization ability of CNN spatio-temporal dynamics, optimal binary and reconstruction image can be obtained. However, in the conventional SD-CNN, the Gaussian LPF, whose coefficients are real number, is used as the A-template. This filter coefficients requirement is one of major factors that restricts a hardware implementation. In this paper, to deal with abovementioned limitation difficulty, a standard 2-D LPF is used for the A-template, and the effectiveness of the proposed method is confirmed by the experimental results.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Σ-Δ Modulator / Cellular Neural Network / Hardware-Friendly Model / Image Reconstruction
Paper # NLP2008-155
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Conference Information
Committee NLP
Conference Date 2009/3/3(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Hardware Implementable Model of Sigma-Delta Cellular Neural Network
Sub Title (in English)
Keyword(1) Σ-Δ Modulator
Keyword(2) Cellular Neural Network
Keyword(3) Hardware-Friendly Model
Keyword(4) Image Reconstruction
1st Author's Name Hisashi AOMORI
1st Author's Affiliation Department of Electrical and Electronics Engineering, Sophia University()
2nd Author's Name Yuki NAITO
2nd Author's Affiliation Department of Electrical and Electronics Engineering, Sophia University
3rd Author's Name Mamoru TANAKA
3rd Author's Affiliation Department of Electrical and Electronics Engineering, Sophia University
Date 2009-03-10
Paper # NLP2008-155
Volume (vol) vol.108
Number (no) 477
Page pp.pp.-
#Pages 5
Date of Issue