Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Journal Basic Information
Journal DOI :
Electronics and Telecommunications Research Institute
Editor in Chief :
Volume & Issues
Volume 22, Issue 4 - Dec 2000
Volume 22, Issue 3 - Sep 2000
Volume 22, Issue 2 - Jun 2000
Volume 22, Issue 1 - Mar 2000
Selecting the target year
A Radial Basis Function Approach to Pattern Recognition and Its Applications
Shin, Mi-Young ; Park, Chee-Hang ;
ETRI Journal, volume 22, issue 2, 2000, Pages 1~1
Pattern recognition is one of the most common problems encountered in engineering and scientific disciplines, which involves developing prediction or classification models from historic data or training samples. This paper introduces a new approach, called the Representational Capability (RC) algorithm, to handle pattern recognition problems using radial basis function (RBF) models. The RC algorithm has been developed based on the mathematical properties of the interpolation and design matrices of RBF models. The model development process based on this algorithm not only yields the best model in the sense of balancing its parsimony and generalization ability, but also provides insights into the design process by employing a design parameter (
). We discuss the RC algorithm and its use at length via an illustrative example. In addition, RBF classification models are developed for heart disease diagnosis.
Cross-talk Cancellation Algorithm for 3D Sound Reproduction
Kim, Hyoun-Suk ; Kim, Poong-Min ; Kim, Hyun-Bin ;
ETRI Journal, volume 22, issue 2, 2000, Pages 11~11
If the right and left signals of a binaural sound recording are reproduced through loudspeakers instead of a headphone, they are inevitably mixed during their transmission to the ears of the listener. This degrades the desired realism in the sound reproduction system, which is commonly called 'cross-talk.' A 'cross-talk canceler' that filters binaural signals before they are sent to the sound sources is needed to prevent cross-talk. A cross-talk canceler equalizes the resulting sound around the listener's ears as if the original binaural signal sound is reproduced next to the ears of listener. A cross-talk canceler is also a solution to the problem-how binaural sound is distributed to more than 2 channels that drive sound sources. This paper presents an effective way of building a cross-talk canceler in which geometric information, including locations of the listener and multiple loudspeakers, is divided into angular information and distance information. The presented method makes a database in an off-line way using an adaptive filtering technique and Head Related Transfer Functions. Though the database is mainly concerned about the situation where loudspeakers are located on a standard radius from the listener, it can be used for general radius cases after a distance compensation process, which requires a small amount of computation. Issues related to inverting a system to build a cross-talk canceler are discussed and numerical results explaining the preferred configuration of a sound reproduction system for stereo loudspeakers are presented.
An Algorithm for Predicting the Relationship between Lemmas and Corpus Size
Yang, Dan-Hee ; Gomez, Pascual Cantos ; Song, Man-Suk ;
ETRI Journal, volume 22, issue 2, 2000, Pages 20~20
Much research on natural language processing (NLP), computational linguistics and lexicography has relied and depended on linguistic corpora. In recent years, many organizations around the world have been constructing their own large corporal to achieve corpus representativeness and/or linguistic comprehensiveness. However, there is no reliable guideline as to how large machine readable corpus resources should be compiled to develop practical NLP software and/or complete dictionaries for humans and computational use. In order to shed some new light on this issue, we shall reveal the flaws of several previous researches aiming to predict corpus size, especially those using pure regression or curve-fitting methods. To overcome these flaws, we shall contrive a new mathematical tool: a piecewise curve-fitting algorithm, and next, suggest how to determine the tolerance error of the algorithm for good prediction, using a specific corpus. Finally, we shall illustrate experimentally that the algorithm presented is valid, accurate and very reliable. We are confident that this study can contribute to solving some inherent problems of corpus linguistics, such as corpus predictability, compiling methodology, corpus representativeness and linguistic comprehensiveness.
An Efficient Content-Based High-Dimensional Index Structure for Image Data
Lee, Jang-Sun ; Yoo, Jae-Soo ; Lee, Seok-Hee ; Kim, Myung-Joon ;
ETRI Journal, volume 22, issue 2, 2000, Pages 32~32
The existing multi-dimensional index structures are not adequate for indexing higher-dimensional data sets. Although conceptually they can be extended to higher dimensionalities, they usually require time and space that grow exponentially with the dimensionality. In this paper, we analyze the existing index structures and derive some requirements of an index structure for content-based image retrieval. We also propose a new structure, for indexing large amount of point data in a high-dimensional space that satisfies the requirements. in order to justify the performance of the proposed structure, we compare the proposed structure with the existing index structures in various environments. We show, through experiments, that our proposed structure outperforms the existing structures in terms of retrieval time and storage overhead.