Bautista, I., Sarkar, S., & Bhanja, S. (2020). MatlabHTM: A sequence
memory model of neocortical layers for anomaly detection.
SoftwareX,
11, 100491.
Abstract
Many
models based on the operation of the neocortex, which is the center of
brain intelligence, are emerging. The Hierarchical Temporal Memory (HTM)
model is a unique intermediate level model of the neocortex’s layered
substructures. The hypothesis is that these layers build temporal models
of sequences of observations and/or motor signals, i.e., build a
sequence memory. Implementations of this model exist in Python, C++ and
Java. However, those implementations are quite cumbersome to use, as
they depend on many other packages. This paper presents a lean,
standalone, easy to modify MATLAB implementation. The performance
results from processing the Numenta Anomaly Benchmark (NAB) demonstrate
the fidelity of matlabHTM.
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