An Application of Hierarchical Temporal Memory (HTM) | A study into the field of Neuromorphic Engineering and an application of the theory of Hierarchial Temporal Memory

Ashley Liddiard (u. a.)

ISBN 10: 3847301764 / ISBN 13: 9783847301769

Published by LAP LAMBERT Academic Publishing, 2011

About this Item

An Application of Hierarchical Temporal Memory (HTM) | A study into the field of Neuromorphic Engineering and an application of the theory of Hierarchial Temporal Memory | Ashley Liddiard (u. a.) | Taschenbuch | 104 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783847301769 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 106672981

Bibliographic Details

• Title: An Application of Hierarchical Temporal Memory (HTM) | A study into the field of Neuromorphic Engineering and an application of the theory of Hierarchial Temporal Memory
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2011
• Language: English
• ISBN 10: 3847301764
• ISBN 13: 9783847301769
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 7D millimeters 220 millimeters width by 150 millimeters height by 7 millimeters depth
• Weight: 173 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

While a number of neuromorphic studies have been based on understanding and building the brain in software and hardware, a recent theory has been presented from a high level, top down approach, with the view of understanding how the human brain performs higher reasoning, and then designing software infrastructure based on that theory – namely Hierarchical Temporal Memory (HTM). Current opinion raises question marks as to whether this theory is sound, feasible, coherent, logical and correct. This work aims to, if not answer some of those questions, at least get closer to understanding the brain and therefore implementing HTM theory in software for further use in an embedded environment. The final output of this thesis is a Hierarchical Temporal node, designed in software, and demonstrating learning using pseudo-random input sensory data and the spatial temporal framework.

About the Author

Ashley lives with her husband in Port Elizabeth and is under full time employ at the Volkswagen production plant in Uitenhage, she continues onto a PhD in engineering. Prof. J Tapson was the inspiration and supervision for this piece, having recently taken a post at the University of Sydney and Robyn Verrinder is at the University of Cape Town.