HTM SPATIAL POOLER WITH TEMPORAL AGGREGATION
This is an open source software framework that attempts to implement most of the ideas about machine intelligence based on the Numenta Inc. Hierarchical Temporal Memory Spatial Pooler theory. It deals with the problem of dimensionality reduction and data associations via temporal aggregation. Use this framework for classifying sequential time series, making sequential predictions and for pattern recognition problems.
Cite As
EN Osegi (2024). HTM SPATIAL POOLER WITH TEMPORAL AGGREGATION (https://www.mathworks.com/matlabcentral/fileexchange/68442-htm-spatial-pooler-with-temporal-aggregation), MATLAB Central File Exchange. Retrieved .
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- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Dimensionality Reduction and Feature Extraction >
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Acknowledgements
Inspired by: HTM-MAT Minimalist HTM Cortical Learning Algorithm
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