A Configurable Digital Cellular Neural Network with Template Decomposition

作者：Yu Sung Nien^*; Lin Chien Nan; Hsu Yun Kai

来源：Circuits, Systems, and Signal Processing, 2011, 30(3): 463-482.

DOI：10.1007/s00034-010-9221-5

• Digital cellular neutral network
• Template decomposition
• Embedded system
• Silicon intellectual property

A configurable digital cellular neural network (DCNN) with decomposable templates is presented. A template decomposition method based on physical circuit decomposition and synthesis is proposed to meet the large template requirement in CNN. The complexity of the template decomposition scheme is only O(aOE(2n+1)/3aOE parts per thousand(2)), which is significantly reduced when compared to the other methods in the literature. Moreover, the proposed method supports both binary and gray-scale images.
The silicon intellectual property (SIP) concept is employed in the design and a friendly graphical user interface (GUI) is developed to facilitate the operation. When implemented on an embedded system with Virtex II XC2V2000 chip, the DCNN is realized with 48014 gates at 18-bit data format and can run at an optimal frequency of 90 MHz. The result outperforms the other approaches to implement DCNN with much reduced gate counts and higher working frequency.

• 出版日期2011-6