TY - GEN
T1 - Application of fuzzy hypothesis testing to signal integration
AU - Leung, S. W.
AU - Minett, J. W.
AU - Lee, M. K.
PY - 2000
Y1 - 2000
N2 - A method of fuzzy likelihood-ratio hypothesis testing is applied to binary signal integration. Imprecise parameters of the distribution under each hypothesis are modeled as fuzzy numbers. The false alarm rate and detection rate are therefore also imprecise. The effects of parameter imprecision on integration performance are examined using an example; the method is applied to envelope detection and integration of fixed amplitude signals in additive white Gaussian noise. For low parameter imprecision, the integration system produces performance which is nearly crisp. However, as parameter imprecision increases significantly, the performance quickly becomes so imprecise that the system may no longer be of practical use.
AB - A method of fuzzy likelihood-ratio hypothesis testing is applied to binary signal integration. Imprecise parameters of the distribution under each hypothesis are modeled as fuzzy numbers. The false alarm rate and detection rate are therefore also imprecise. The effects of parameter imprecision on integration performance are examined using an example; the method is applied to envelope detection and integration of fixed amplitude signals in additive white Gaussian noise. For low parameter imprecision, the integration system produces performance which is nearly crisp. However, as parameter imprecision increases significantly, the performance quickly becomes so imprecise that the system may no longer be of practical use.
UR - http://www.scopus.com/inward/record.url?scp=0033715488&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0033715488&origin=recordpage
M3 - 32_Refereed conference paper (with ISBN/ISSN)
VL - 1
SP - 181
EP - 184
BT - IEEE International Conference on Fuzzy Systems
PB - IEEE
T2 - FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems
Y2 - 7 May 2000 through 10 May 2000
ER -