Last edited by Zulkirisar
Monday, July 27, 2020 | History

5 edition of Vector quantization and signal compression found in the catalog.

Vector quantization and signal compression

by Allen Gersho

  • 328 Want to read
  • 21 Currently reading

Published by Kluwer Academic Publishers in Boston .
Written in English

    Subjects:
  • Signal processing -- Digital techniques.,
  • Data compression (Telecommunication),
  • Coding theory.

  • Edition Notes

    Includes bibliographical references (p. 691-719) and index.

    Statementby Allen Gersho, Robert M. Gray.
    SeriesThe Kluwer international series in engineering and computer science ;, SECS 159., Communications and information theory, Kluwer international series in engineering and computer science ;, SECS 159., Kluwer international series in engineering and computer science.
    ContributionsGray, Robert M., 1943-
    Classifications
    LC ClassificationsTK5102.5 .G45 1991
    The Physical Object
    Paginationxxii, 732 p. :
    Number of Pages732
    ID Numbers
    Open LibraryOL1549030M
    ISBN 100792391810
    LC Control Number91028580

    Vector Quantization and Signal Compression av Allen Gersho, Robert M Gray. Inbunden Engelska, Köp. Spara som favorit Skickas inom vardagar. This book is devoted to the theory and practice of signal compression, i. e., data compression applied to signals such as speech, audio, images, and video signals (excluding. With respect to the contents of the book, it has almost everything you may want to know about Vector (and even Scalar) quantization and Signal compression. It was a great help while I was writing my doctoral thesis. Gray is probably one of the most respected authorities in the field. Read more.5/5(2).

    A. Gersho and R. M. Gray, Vector Quantization and Signal Compression, Kluwer Academic Press/Springer, Interest Areas. Formerly Quantization theory and algorithms, Information theory, Statistical signal processing, Signal compression and classification. Now mostly sailing, hiking, historical research and writing. Historical articles. Vector Quantization and Signal Compression (The Springer International Series in Engineering and Computer Science) Gersho, Allen Gray, Robert M. Springer / Hardcover / Pages isbn / isbn Book / Textbook Details Add to Comparison Cart.

    In this article, we make a comparative study for a new approach compression between discrete cosine transform (DCT) and discrete wavelet transform (DWT). We seek the transform proper to vector quantization to compress the EMG signals. To do this, we initially associated vector quantization and DCT, then vector quantization and DWT. The coding phase is made by the SPIHT coding (set . We can do the same with quantization. The vector quantization procedure is shown in this block diagram. It is a rather straight forward procedure. Given a one dimensional or a two dimensional signal, such as an image, a number of samples or pixels in a small block are considered at once and they are grouped into a vector.


Share this book
You might also like
Britain

Britain

Old buildings; Sacramento & San Joaquin Counties.

Old buildings; Sacramento & San Joaquin Counties.

The Mystic Rose (Celtic Crusades (Paperback))

The Mystic Rose (Celtic Crusades (Paperback))

Manilal Dvivedi

Manilal Dvivedi

Religious liberty in the sixteenth century

Religious liberty in the sixteenth century

Berlin

Berlin

World Conference on Lung Cancer

World Conference on Lung Cancer

HADY-1, a FORTRAN program for the compressible stability analysis of three-dimensional boundary layers

HADY-1, a FORTRAN program for the compressible stability analysis of three-dimensional boundary layers

Illustrated catalogue of etchings by American artists for sale by Frederick Keppel & Co., 4 East 39th Street, New York.

Illustrated catalogue of etchings by American artists for sale by Frederick Keppel & Co., 4 East 39th Street, New York.

Paris as it is

Paris as it is

Efruz Bey

Efruz Bey

Didache

Didache

Vector quantization and signal compression by Allen Gersho Download PDF EPUB FB2

This book is devoted to the theory and practice of signal compression, i. e., data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such as financial data or general­ purpose computer data).Cited Vector quantization and signal compression book Compression in general is intended to provide efficient representations of data while preserving the essential information contained in the data.

This book is devoted to the theory and practice of signal compression, i. e., data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such as financial data or general­ purpose computer data). Vector Quantization and Signal Compression (The Springer International Series in Engineering and Computer Science Book ) - Kindle edition by Gersho, Allen, Gray, Robert M.

Download it once and read it on your Kindle device, PC, phones or tablets/5(3). Vector Quantization and Signal Compression book. Read reviews from world’s largest community for readers. Herb Caen, a popular columnist for the San Fran /5.

This book is devoted to the theory and practice of signal compression, i. e., data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such. This book is devoted to the theory and practice of signal compression, i.

e., data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such as financial data or general purpose computer data)/5(4). Salleh M and Soraghan J () A new multistage lattice vector quantization with adaptive subband thresholding for image compression, EURASIP Journal on Advances in Signal Processing,(), Online publication date: 1-Jan Vector quantization and signal compression / by Allen Gersho, Robert M.

Gray. -- (K1uwer international series in engineering and computer science ; SECS ) Includes bibliographical references and index. ISBN ISBN (eBook) DOI /.

Rate this book. Clear rating. 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars. An Introduction to Statistical Signal Processing by. Robert M. Gray, Lee D. Davisson.

Vector Quantization and Signal Compression by. Allen Gersho, Robert M. Gray/5(2). Principles of lossless compression are covered, as are various entropy coding techniques, including Huffman coding, arithmetic coding and Lempel-Ziv coding.

Scalar and vector quantization and trellis coding are thoroughly explained, and a full chapter is devoted to mathematical transformations including the KLT, DCT and wavelet transforms.

This book is devoted to the theory and practice of signal compression, i. e., data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such as financial data or general­ purpose computer data).Author: Allen Gersho.

This book is devoted to the theory and practice of signal compression, i. e., data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such as financial data or general­ purpose computer data).

Overview. This book is devoted to the theory and practice of signal compression; i.e. data compression applied to signals such as speech, audio, images and video signals. The emphasis is on the conversion of analog waveforms into efficient digital representations and on the compression of digital information into the fewest possible : Springer US.

Vector Quantization and Signal Compression by Allen Gersho,available at Book Depository with free delivery worldwide/5(4). Title: Microsoft PowerPoint - Ch_10_1 VQ Description Author: mfowler Created Date: 2/9/ AM. III Vector Coding.- 10 Vector Quantization I.- Introduction.- Structural Properties and Characterization.- Measuring Vector Quantizer Performance.- Nearest Neighbor Quantizers.- Lattice Vector Quantizers.- High Resolution Distortion Approximations.- Problems.- 11 Vector Quantization II.- Introduction.- Vector quantization is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors.

It was originally used for data compression. It works by dividing a large set of points into groups having approximately the same number of points closest to them. Each group is represented by its centroid point, as in k-means and some. This book presents tools and algorithms required to compress and uncompress signals such as speech and music.

These algorithms are largely used in mobile phones, DVD players, and HDTV sets. The book begins by presenting the standard tools used in compression systems: scalar and vector quantization, predictive quantization, transform.

This book is devoted to the theory and practice of signal compression, i. e., data compression applied to signals such as speech, audio, images, and video signals (excluding other data types such as financial data or generalƯ purpose computer data).

Free shipping on orders of $35+ from Target. Read reviews and buy Vector Quantization and Signal Compression - (The Springer International Engineering Computer Science) by Allen Gersho & Robert M Gray at Target.

Get it today with Same Day Delivery, Order Pickup or Drive : $. Vector quantization (VQ) is a kind of signal compression method. CELP coding uses the VQ method to compress data, such as an excitation signal, LPCs, and codebook gain. VQ concerns the mapping in a multidimensional space from a (possibly continuous-amplitude) source ensemble to a discrete ensemble.This book presents tools and algorithms required to compress/uncompress signals such as speech and music.

These algorithms are largely used in mobile phones, DVD players, HDTV sets, etc. In a first rather theoretical part, this book presents the standard tools used in compression systems: scalar and vector quantization, predictive quantization.Vector Quantization.

Vector quantization is a lossy compression technique used in speech and image coding. In scalar quantization, a scalar value is selected from a finite list of possible values to represent a sample.

In vector quantization, a vector is selected from a finite list of possible vectors to represent an input vector of.