From bidirectional associative memory to a noise-tolerant, robust protein processor associative memory

Omer Qadir*, Jerry Liu, Gianluca Tempesti, Jon Timmis, Andy Tyrrell

*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

10 Dyfyniadau(SciVal)

Crynodeb

Protein Processor Associative Memory (PPAM) is a novel architecture for learning associations incrementally and online and performing fast, reliable, scalable hetero-associative recall. This paper presents a comparison of the PPAM with the Bidirectional Associative Memory (BAM), both with Kosko's original training algorithm and also with the more popular Pseudo-Relaxation Learning Algorithm for BAM (PRLAB). It also compares the PPAM with a more recent associative memory architecture called SOIAM. Results of training for object-avoidance are presented from simulations using player/stage and are verified by actual implementations on the E-Puck mobile robot. Finally, we show how the PPAM is capable of achieving an increase in performance without using the typical weighted-sum arithmetic operations or indeed any arithmetic operations.

Iaith wreiddiolSaesneg
Tudalennau (o-i)673-693
Nifer y tudalennau21
CyfnodolynArtificial Intelligence
Cyfrol175
Rhif cyhoeddi2
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - Chwef 2011

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