Pregled bibliografske jedinice broj: 355404
Relevance of Qualitative Subjective Visual Attributes to Signal Categorization
Relevance of Qualitative Subjective Visual Attributes to Signal Categorization // The 14th IEEE Mediterranean Electrozechnical Conference Proceedings / Capolino, Gerard-Andre (ur.).
Ajaccio: Institute of Electrical and Electronics Engineers (IEEE), 2008. str. 835-840 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 355404 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Relevance of Qualitative Subjective Visual Attributes to Signal Categorization
Autori
Bogunović, Nikola ; Jagnjć, Željko ; Jović, Franjo
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
The 14th IEEE Mediterranean Electrozechnical Conference Proceedings
/ Capolino, Gerard-Andre - Ajaccio : Institute of Electrical and Electronics Engineers (IEEE), 2008, 835-840
ISBN
978-1-4244-1633-2
Skup
The 14th IEEE Mediterranean Electrozechnical Conference
Mjesto i datum
Ajaccio, Francuska, 05.05.2008. - 07.05.2008
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Discrete-space ; Feature extraction ; Pattern classification ; Qualitative analysis ; Time series classification
Sažetak
Signals represented by their proper (in the sense of Nyquist-Shannon theorem) sampled values as time-series are commonly categorized by objective features such as amplitude and frequency distribution. The paper presents a novel signal classification method based on full difference expansion, mapping this expansion to qualitative space and extraction of subjective visual attributes from the qualitative space. The full qualitative difference expansion yields a vector that conveys total information on the variation of the particular signal represented by time-series and can be seen as a single point in n-dimensional discrete-space. From such a discrete-space, symbolic and numeric features are subjectively extracted and used for the decision tree construction that is consequently used in signal classification. The proposed method was tested in the context of the standard Control Chart Pattern data, which are time-series used in Statistical Process Control. The results are compared with other similar methods.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
036-0362980-1921 - Računalne okoline za sveprisutne raspodijeljene sustave (Srbljić, Siniša, MZO ) ( CroRIS)
098-0982560-2563 - Algoritmi strojnog učenja i njihova primjena (Gamberger, Dragan, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Institut "Ruđer Bošković", Zagreb
Profili:
Nikola Bogunović
(autor)