  Advances in machine learning and neuromorphic systems are fuelled by the
development of architectures required for these applications, such as content
addressable memory. In an attempt to address this need, this paper presents a
new RRAM tuned window comparator, building upon existing work in reconfigurable
computing. The circuit uses a low component count at 6T2R2M, comparable with
the most compact existing cells of this type. This paper will present this
design, demonstrating its operation with TiOx memristive devices, showing its
controllability and specificity. This paper will then simulate the energy
dissipated in its operation, showing it to be below 100pJ per test, comparable
to existing works.

Signal Processing