Enhanced Boolean Correlation Matrix Memory
This work addresses a specific bottleneck in binary memory systems, with potential applications in fields like steganography and Hopfield networks, but it appears incremental as it builds on existing CMM methods.
The paper tackles the problem of improving Boolean Correlation Matrix Memory (CMM) for binary memories by introducing a Boolean Orthonormalization Process (BOP) to convert non-orthonormal binary vectors into an orthonormal basis, resulting in enhanced performance.
This paper introduces an Enhanced Boolean version of the Correlation Matrix Memory (CMM), which is useful to work with binary memories. A novel Boolean Orthonormalization Process (BOP) is presented to convert a non-orthonormal Boolean basis, i.e., a set of non-orthonormal binary vectors (in a Boolean sense) to an orthonormal Boolean basis, i.e., a set of orthonormal binary vectors (in a Boolean sense). This work shows that it is possible to improve the performance of Boolean CMM thanks BOP algorithm. Besides, the BOP algorithm has a lot of additional fields of applications, e.g.: Steganography, Hopfield Networks, Bi-level image processing, etc. Finally, it is important to mention that the BOP is an extremely stable and fast algorithm.