Title :
Biology Inspired Approximate Data Representation for Signal Processing, Soft Computing and Control Applications
Author_Institution :
Univ. of Ottawa, Ottawa
Abstract :
This paper reviews basics, similarities, and applications of two well-known biology inspired approximate data representation modalities: stochastic data representation and fuzzy linguistic variables.
Keywords :
data structures; fuzzy logic; neural nets; signal processing; biology inspired approximate data representation; control applications; fuzzy linguistic variables; signal processing; soft computing; stochastic data representation; Biological control systems; Biology computing; Biomedical signal processing; Computer applications; Fuzzy control; Fuzzy logic; Humans; Quantization; Stochastic processes; Stochastic resonance; dithering; fuzzy logic; fuzzy logic control; neural networks; random-pulse machines; stochastic computing;
Conference_Titel :
Intelligent Signal Processing, 2007. WISP 2007. IEEE International Symposium on
Conference_Location :
Alcala de Henares
Print_ISBN :
978-1-4244-0830-6
Electronic_ISBN :
978-1-4244-0830-6
DOI :
10.1109/WISP.2007.4447532
