REALIZATION OF OTA-C UNIVERSAL FILTER BASED ON Q- FACTOR
Published In: 3RD INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, ELECTRONICS AND COMMUNICATION
Author(s): M. M. MUTSADDI , MANJULA V. KATAGERI , RAJESHWARI S. MATHAD
Abstract: A second order OTA-C filter based on OTA integrator and register is selected as a suitable structure in the design of universal filter by selecting proper inputs VA, VB and Vc. This selection reflects the Q factor sensitization in obtaining -3dB frequency in low-pass, high-pass, band-pass and band-reject filter structures. The variation in the values of C1 and C2 and their contribution in the values of Q factors is studied. The studied structure is superior to the other types of filters at radio and microwave frequencies in communication system.
- Publication Date: 11-Oct-2015
- DOI: 10.15224/978-1-63248-064-4-26
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A SEMANTIC APPROACH FOR TEXT CLUSTERING USING WORDNET BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS
Published In: 3RD INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, ELECTRONICS AND COMMUNICATION
Author(s): HAN HEE HAHM , JONG JOO LEE , SOON CHEOL PARK
Abstract: In this paper, we propose a method of Multi- Objective Genetic Algorithms (MOGAs), NSGA-II and SPEA2, for document clustering with semantic similarity measures based on WordNet. The MOGAs showed a high performance compared to other clustering algorithms. The main problem in the application of MOGAs for document clustering in the Vector Space Model (VSM) is that it ignores relationships between important terms or words. The hierarchical structure of WordNet as thesaurus-based ontology is an effective technique, which is used in semantic similarity measure. We tested these algorithms on Reuter-21578 collection data sets and compared them with Genetic Algorithms (GA) in conjunction with the semantic similarity measures based on WordNet. Also, we used F-measure to evaluate the performance of these clustering algorithms. The experimental results show that the performance of MOGAs based on WordNet is superior to those of the other clustering algorithms in the same similarity environments.
- Publication Date: 11-Oct-2015
- DOI: 10.15224/978-1-63248-064-4-27
- Views: 0
- Downloads: 0