The Receptor Density Algorithm

TY - JOUR

T1 - The Receptor Density Algorithm

AU - Owens, N

AU - Greensted, Andrew J.

AU - Timmis, Jon

AU - Tyrrell, Andy

PY - 2013/4/15

Y1 - 2013/4/15

N2 - This paper describes the biological and theoretical foundations of a new Artificial Immune System the Receptor Density Algorithm. The algorithm is developed with inspiration from T cell signalling processes and has application in anomaly detection. Connections between the Receptor Density Algorithm and kernel density estimation with exponential smoothing are demonstrated. Finally, the paper evaluates the algorithm’s performance on two types of anomaly detection problem.

AB - This paper describes the biological and theoretical foundations of a new Artificial Immune System the Receptor Density Algorithm. The algorithm is developed with inspiration from T cell signalling processes and has application in anomaly detection. Connections between the Receptor Density Algorithm and kernel density estimation with exponential smoothing are demonstrated. Finally, the paper evaluates the algorithm’s performance on two types of anomaly detection problem.

UR - http://www.scopus.com/inward/record.url?scp=84875825864&partnerID=8YFLogxK

U2 - 10.1016/j.tcs.2012.10.057

DO - 10.1016/j.tcs.2012.10.057

M3 - Article

SN - 0304-3975

VL - 481

SP - 51073

JO - Theoretical Computer Science

JF - Theoretical Computer Science

IS - n/a

ER -