Evaluation of morphological texture features for real-time biological signal classification /
are presented.
| Main Author: | |
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| Format: | Thesis eBook |
| Language: | English |
| Published: |
[Place of publication not identified] :
[publisher not identified] ;
1998.
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| Subjects: | |
| Online Access: | Link to OAKTrust copy |
| Summary: | are presented. biological sound signals is examined. This is done by carrying out a comparative study with two other sets of characteristics and have been used for signal classification. features for signal classification in general and biological features used in signal classification - the widely used However, little has been done in using morphological texture Linear Predictive Coefficients (LPCS) and the statistical Model (HMM) is used as the classifier. Both the LPCs and the morphological texture features are implemented in real-time on a DSP processor and their respective classification rates shape features of the frequency spectrum. The Hidden Markov sound signal classification in particular. In this thesis, Texture features of a signal reflect its shape the performance of these features in the classification of |
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| Item Description: | "Major subject: Electrical Engineering". Vita. |
| Physical Description: | xi, 102 leaves : illustrations ; 28 cm. Also available online. Issued also on microfiche from Lange Micrographics. |
| Bibliography: | Includes bibliographical references: pages 69-70. |