Abstract
The analog CMOS circuit realization of cellular neural networks with transconductance elements is presented. This realization can be easily adapted to various types of applications in image processing just by choosing the appropriate transconductance parameters according to the predetermined coefficients. The effectiveness of the designed circuits for connected component detection is shown by HSPICE simulations. For fixed function cellular neural network circuits, the number of transistors is reduced further by using multi-input transconductance elements.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.