Design Printed-Circuit-Board Antennas Using Image Classifier and Fixed Dimension Components

To extend antenna designs on printed circuit boards for more engineers of interest, we propose a new simple method that models PCB antennas by a few basic components. By taking two separate steps to decide their geometrical properties, antenna prototypes can be facilitated with no experience required. Random sampling techniques are used in selecting high quality candidates. A novel image-based classifier is introduced to convolutional neural networks to further filtering out the premium topological structures. Examples from wearable products have been chosen to examine the entire workflow. Their final designs are realistic and their performance metrics are not inferior to the ones designed by experienced engineers.