Efficient algorithms for discrete wavelet transform: with applications to denoising and fuzzy inference systems
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London [u.a.]
Springer
2013
|
| Schriftenreihe: | SpringerBriefs in computer science
|
| Online-Zugang: | BTU01 FHA01 FHM01 FHN01 FKE01 UBG01 UBR01 UBT01 UBW01 UER01 UPA01 Volltext Inhaltsverzeichnis Abstract |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9781447149408 9781447149415 |
| DOI: | 10.1007/978-1-4471-4941-5 |
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Datensatz im Suchindex
| _version_ | 1804150161051484160 |
|---|---|
| adam_text | EFFICIENT ALGORITHMS FOR DISCRETE WAVELET TRANSFORM
/ SHUKLA, K. K.
: 2013
TABLE OF CONTENTS / INHALTSVERZEICHNIS
INTRODUCTION
FILTER BANKS AND DWT
FINITE PRECISION ERROR MODELING AND ANALYSIS
PVM IMPLEMENTATION OF DWT-BASED IMAGE DENOISING
DWT-BASED POWER QUALITY CLASSIFICATION
CONCLUSIONS AND FUTURE DIRECTIONS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
EFFICIENT ALGORITHMS FOR DISCRETE WAVELET TRANSFORM
/ SHUKLA, K. K.
: 2013
ABSTRACT / INHALTSTEXT
TRANSFORMS ARE AN IMPORTANT PART OF AN ENGINEER’S TOOLKIT FOR SOLVING
SIGNAL PROCESSING AND POLYNOMIAL COMPUTATION PROBLEMS. IN CONTRAST TO
THE FOURIER TRANSFORM-BASED APPROACHES WHERE A FIXED WINDOW IS USED
UNIFORMLY FOR A RANGE OF FREQUENCIES, THE WAVELET TRANSFORM USES SHORT
WINDOWS AT HIGH FREQUENCIES AND LONG WINDOWS AT LOW FREQUENCIES. THIS
WAY, THE CHARACTERISTICS OF NON-STATIONARY DISTURBANCES CAN BE MORE
CLOSELY MONITORED. IN OTHER WORDS, BOTH TIME AND FREQUENCY INFORMATION
CAN BE OBTAINED BY WAVELET TRANSFORM. INSTEAD OF TRANSFORMING A PURE
TIME DESCRIPTION INTO A PURE FREQUENCY DESCRIPTION, THE WAVELET
TRANSFORM FINDS A GOOD PROMISE IN A TIME-FREQUENCY DESCRIPTION. DUE TO
ITS INHERENT TIME-SCALE LOCALITY CHARACTERISTICS, THE DISCRETE WAVELET
TRANSFORM (DWT) HAS RECEIVED CONSIDERABLE ATTENTION IN DIGITAL SIGNAL
PROCESSING (SPEECH AND IMAGE PROCESSING), COMMUNICATION, COMPUTER
SCIENCE AND MATHEMATICS. WAVELET TRANSFORMS ARE KNOWN TO HAVE EXCELLENT
ENERGY COMPACTION CHARACTERISTICS AND ARE ABLE TO PROVIDE PERFECT
RECONSTRUCTION. THEREFORE, THEY ARE IDEAL FOR SIGNAL/IMAGE PROCESSING.
THE SHIFTING (OR TRANSLATION) AND SCALING (OR DILATION) ARE UNIQUE TO
WAVELETS. ORTHOGONALITY OF WAVELETS WITH RESPECT TO DILATIONS LEADS TO
MULTIGRID REPRESENTATION. THE NATURE OF WAVELET COMPUTATION FORCES US TO
CAREFULLY EXAMINE THE IMPLEMENTATION METHODOLOGIES. AS THE COMPUTATION
OF DWT INVOLVES FILTERING, AN EFFICIENT FILTERING PROCESS IS ESSENTIAL
IN DWT HARDWARE IMPLEMENTATION. IN THE MULTISTAGE DWT, COEFFICIENTS ARE
CALCULATED RECURSIVELY, AND IN ADDITION TO THE WAVELET DECOMPOSITION
STAGE, EXTRA SPACE IS REQUIRED TO STORE THE INTERMEDIATE COEFFICIENTS.
HENCE, THE OVERALL PERFORMANCE DEPENDS SIGNIFICANTLY ON THE PRECISION OF
THE INTERMEDIATE DWT COEFFICIENTS. THIS WORK PRESENTS NEW IMPLEMENTATION
TECHNIQUES OF DWT, THAT ARE EFFICIENT IN TERMS OF COMPUTATION
REQUIREMENT, STORAGE REQUIREMENT, AND WITH BETTER SIGNAL-TO-NOISE RATIO
IN THE RECONSTRUCTED SIGNAL
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
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| spelling | Shukla, K. K. Verfasser aut Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems K. K. Shukla ; Arvind K. Tiwari London [u.a.] Springer 2013 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier SpringerBriefs in computer science Tiwari, Arvind K. Verfasser aut https://doi.org/10.1007/978-1-4471-4941-5 Verlag Volltext Springer Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025858729&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Springer Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025858729&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Abstract |
| spellingShingle | Shukla, K. K. Tiwari, Arvind K. Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems |
| title | Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems |
| title_auth | Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems |
| title_exact_search | Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems |
| title_full | Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems K. K. Shukla ; Arvind K. Tiwari |
| title_fullStr | Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems K. K. Shukla ; Arvind K. Tiwari |
| title_full_unstemmed | Efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems K. K. Shukla ; Arvind K. Tiwari |
| title_short | Efficient algorithms for discrete wavelet transform |
| title_sort | efficient algorithms for discrete wavelet transform with applications to denoising and fuzzy inference systems |
| title_sub | with applications to denoising and fuzzy inference systems |
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