Speech coding using spline wavelet and adaptive backward prediction /
achievements in wavelet applications have been obtained in
| Main Author: | |
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| Format: | Thesis eBook |
| Language: | English |
| Published: |
[Place of publication not identified] :
[publisher not identified] ;
1994.
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| Subjects: | |
| Online Access: | Link to OAKTrust copy |
| Summary: | achievements in wavelet applications have been obtained in adaptive quantizer algorithm based on the pdf-optimized algorithm is proven to effectively encode the wavelet applied ADPCM (Adaptive Differential Pulse Code Modulation) applying wavelet techniques in speech coding. are. quite different from speech signals, a new nonuniform coefficients. Finally, the coding system containing both existing wavelet algorithms are modified to fit the fields such as signal detection and image compression, frequency localization for signal processing. Although great given to show that the new design is better than the in real-time mode. In this thesis, the application of quantizer design is introduced. Several comparisons are redesigned to work on the backward mode in this research, the reproduction at a bit rate of 8 Kbps. To achieve this, the requirements of real-time data processing. Furthermore, research effort seems to be lacking in the application of since the input to the coder are wavelet coefficients which speech coding is investigated. The goal of the research is speech signal at a total bit rate of 16 Kbps and intelligible splinewavelets incorporating adaptive backward prediction to take advantage of the multiresolution analysis generated by the wavelet transform in order to provide a high-quality to develop the real-time, moderately complex algorithms which tradictional Jayant's adaptive quantizer (JAQ). Combining it using semi-orthogonal wavelets to speech coding, especially various simulations are presented to show the advantages of wavelet analysis and the developed ADPCM is built up, and Wavelet techniques are well known for providing both time and with the autocorrelation solution predictor, which is |
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| Item Description: | "Major subject: Electrical Engineering". Vita. |
| Physical Description: | xi, 78 leaves : illustrations ; 28 cm. Also available online. |
| Bibliography: | Includes bibliographical references. |