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The Resource Efficient algorithms for discrete wavelet transform : with applications to denoising and fuzzy inference systems, K.K. Shukla, Arvind K. Tiwari
Efficient algorithms for discrete wavelet transform : with applications to denoising and fuzzy inference systems, K.K. Shukla, Arvind K. Tiwari
Resource Information
The item Efficient algorithms for discrete wavelet transform : with applications to denoising and fuzzy inference systems, K.K. Shukla, Arvind K. Tiwari represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item Efficient algorithms for discrete wavelet transform : with applications to denoising and fuzzy inference systems, K.K. Shukla, Arvind K. Tiwari represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
 Summary
 Transforms are an important part of an engineer’s toolkit for solving signal processing and polynomial computation problems. In contrast to the Fourier transformbased 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 nonstationary 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 timefrequency description. Due to its inherent timescale 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 signaltonoise ratio in the reconstructed signal
 Language
 eng
 Extent
 1 online resource (ix, 91 pages)
 Contents

 Introduction
 Filter Banks and DWT
 Finite Precision Error Modeling and Analysis
 PVM Implementation of DWTBased Image Denoising
 DWTBased Power Quality Classification
 Conclusions and Future Directions
 Isbn
 9781447149415
 Label
 Efficient algorithms for discrete wavelet transform : with applications to denoising and fuzzy inference systems
 Title
 Efficient algorithms for discrete wavelet transform
 Title remainder
 with applications to denoising and fuzzy inference systems
 Statement of responsibility
 K.K. Shukla, Arvind K. Tiwari
 Subject

 Mathematics
 Transformations (Mathematics)
 Transformations (Mathematics)
 Transformations (Mathematics)
 Transformations (Mathematics)
 Wavelet Analysis
 Wavelet Analysis
 Wavelets (Mathematics)
 Wavelets (Mathematics)
 Wavelets (Mathematics)
 Wavelets (Mathematics)
 Electronic books
 Electronic resources
 MATHEMATICS  Functional Analysis
 Mathematics
 Language
 eng
 Summary
 Transforms are an important part of an engineer’s toolkit for solving signal processing and polynomial computation problems. In contrast to the Fourier transformbased 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 nonstationary 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 timefrequency description. Due to its inherent timescale 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 signaltonoise ratio in the reconstructed signal
 Cataloging source
 GW5XE
 http://library.link/vocab/creatorDate
 1958
 http://library.link/vocab/creatorName
 Shukla, K. K.
 Image bit depth
 0
 LC call number
 QA403.3
 LC item number
 .S58 2013
 Literary form
 non fiction
 Nature of contents
 dictionaries
 http://library.link/vocab/relatedWorkOrContributorName

 SpringerLink
 Tiwari, Arvind K.
 Series statement
 SpringerBriefs in Computer Science,
 http://library.link/vocab/subjectName

 Wavelet Analysis
 Mathematics
 Wavelets (Mathematics)
 Transformations (Mathematics)
 MATHEMATICS
 Transformations (Mathematics)
 Wavelets (Mathematics)
 Label
 Efficient algorithms for discrete wavelet transform : with applications to denoising and fuzzy inference systems, K.K. Shukla, Arvind K. Tiwari
 Antecedent source
 mixed
 Bibliography note
 Includes bibliographical references
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 Introduction  Filter Banks and DWT  Finite Precision Error Modeling and Analysis  PVM Implementation of DWTBased Image Denoising  DWTBased Power Quality Classification  Conclusions and Future Directions
 Dimensions
 unknown
 Extent
 1 online resource (ix, 91 pages)
 File format
 multiple file formats
 Form of item

 online
 electronic
 Isbn
 9781447149415
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other control number
 10.1007/9781447149415
 Other physical details
 illustrations (some color)
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number

 (OCoLC)826292328
 (OCoLC)ocn826292328
 Label
 Efficient algorithms for discrete wavelet transform : with applications to denoising and fuzzy inference systems, K.K. Shukla, Arvind K. Tiwari
 Antecedent source
 mixed
 Bibliography note
 Includes bibliographical references
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 Introduction  Filter Banks and DWT  Finite Precision Error Modeling and Analysis  PVM Implementation of DWTBased Image Denoising  DWTBased Power Quality Classification  Conclusions and Future Directions
 Dimensions
 unknown
 Extent
 1 online resource (ix, 91 pages)
 File format
 multiple file formats
 Form of item

 online
 electronic
 Isbn
 9781447149415
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other control number
 10.1007/9781447149415
 Other physical details
 illustrations (some color)
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number

 (OCoLC)826292328
 (OCoLC)ocn826292328
Subject
 Mathematics
 Transformations (Mathematics)
 Transformations (Mathematics)
 Transformations (Mathematics)
 Transformations (Mathematics)
 Wavelet Analysis
 Wavelet Analysis
 Wavelets (Mathematics)
 Wavelets (Mathematics)
 Wavelets (Mathematics)
 Wavelets (Mathematics)
 Electronic books
 Electronic resources
 MATHEMATICS  Functional Analysis
 Mathematics
Genre
Member of
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<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.bu.edu/portal/Efficientalgorithmsfordiscretewavelet/DbE4JxP5LQY/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.bu.edu/portal/Efficientalgorithmsfordiscretewavelet/DbE4JxP5LQY/">Efficient algorithms for discrete wavelet transform : with applications to denoising and fuzzy inference systems, K.K. Shukla, Arvind K. Tiwari</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.bu.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.bu.edu/">Boston University Libraries</a></span></span></span></span></div>