TY  - BOOK
AU  - Dimaano, Melanie Rose J. and Quiambao, Crispin V.
AU  - 
ED  - 
ED  - 
ED  - 
ED  - 
SN  - 2
PY  - 2003///.46
CY  - 
PB  - 
KW  - 
KW  - 2
KW  - 0
KW  - 6
KW  - 20
N1  - Undergraduate Thesis: (B.S. in Computer Studies major in Computer Studies) -  Pamantasan ng Lungsod ng Maynila, 2003; 5
N2  - ABSTRACT:  	The exploration of data has been examined for many years now. It has been used to enhance the resolution of images or to complete fragmented data sets. Current extrapolation theories can also be successfully implemented to estimate missing audio data. The major problem, however, is the large amount of audio data samples required for even small time segments. These large data sets result in heavy computational time and memory requirements. These computational requirements often exceed the application constraints. If the input data segment is divided into a group of smaller data segments, computational requirements can be greatly reduced. Reducing computational requirements decreases processing time and enables processing of large data segments, which previously exceeded application limits.  	This study aims to reduce the computational requirements and enables the extrapolation of larger data segments by dividing the known time-domain data segment into several smaller time-domain data segments. Each smaller segment is processed through the extrapolation method and then re-combined to form the main extrapolation. The proponents purpose is to provide a continuous audio stream even in the presence of missing audio data for the listener
ER  -