== Abstract ==

​

In this paper we report on the performance of a coupled oscillator based implementation of the HMAX image-processing pipeline. Within this pipeline we have used coupled oscillator arrays to replace traditional Boolean logic with a Degree-of-Match (DoM) function that measures the L2 distance squared between two vectors in an n-dimensional space. We show that this operation can be used in three stages of the pipeline: 1) as a substitute for convolution in filtering operations, 2) as a computational kernel for pattern matching, and 3) as a distance function in a nearest neighbor classification algorithm. In this study, we have modeled the performance of the latter two and report our recognition results over a test set from the Neo Vision2 image database.

​

​

== Original document ==

​

The different versions of the original document can be found in:

​

* [https://zenodo.org/record/1280246 https://zenodo.org/record/1280246] under the license https://creativecommons.org/share-your-work/public-domain/cc0/

​

* [https://zenodo.org/record/1280246/files/article.pdf https://zenodo.org/record/1280246/files/article.pdf]

​

* [http://xplorestaging.ieee.org/ielx7/6973465/6986048/06986101.pdf?arnumber=6986101 http://xplorestaging.ieee.org/ielx7/6973465/6986048/06986101.pdf?arnumber=6986101],

: [http://dx.doi.org/10.1109/sips.2014.6986101 http://dx.doi.org/10.1109/sips.2014.6986101] under the license cc0

​

* [https://dblp.uni-trier.de/db/conf/sips/sips2014.html#JenningsBGCFCL14 https://dblp.uni-trier.de/db/conf/sips/sips2014.html#JenningsBGCFCL14],

: [https://academic.microsoft.com/#/detail/2003232723 https://academic.microsoft.com/#/detail/2003232723]

​