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J.D. Gibson

Bio: J.D. Gibson is an academic researcher from Texas A&M University. The author has contributed to research in topics: Delta modulation & Speech coding. The author has an hindex of 1, co-authored 1 publications receiving 385 citations.

Papers
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Journal ArticleDOI
J.D. Gibson1
01 Apr 1987

385 citations


Cited by
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Book
31 May 1997
TL;DR: Adaptive Filtering: Algorithms and Practical Implementation may be used as the principle text for courses on the subject, and serves as an excellent reference for professional engineers and researchers in the field.
Abstract: From the Publisher: Adaptive Filtering: Algorithms and Practical Implementation is a concise presentation of adaptive filtering, covering as many algorithms as possible while avoiding adapting notations and derivations related to the different algorithms. Furthermore, the book points out the algorithms which really work in a finite-precision implementation, and provides easy access to the working algorithms for the practicing engineer. Adaptive Filtering: Algorithms and Practical Implementation may be used as the principle text for courses on the subject, and serves as an excellent reference for professional engineers and researchers in the field.

1,294 citations

Journal ArticleDOI
01 Nov 1985
TL;DR: This tutorial review presents the basic concepts employed in vector quantization and gives a realistic assessment of its benefits and costs when compared to scalar quantization, and focuses primarily on the coding of speech signals and parameters.
Abstract: Quantization, the process of approximating continuous-amplitude signals by digital (discrete-amplitude) signals, is an important aspect of data compression or coding, the field concerned with the reduction of the number of bits necessary to transmit or store analog data, subject to a distortion or fidelity criterion. The independent quantization of each signal value or parameter is termed scalar quantization, while the joint quantization of a block of parameters is termed block or vector quantization. This tutorial review presents the basic concepts employed in vector quantization and gives a realistic assessment of its benefits and costs when compared to scalar quantization. Vector quantization is presented as a process of redundancy removal that makes effective use of four interrelated properties of vector parameters: linear dependency (correlation), nonlinear dependency, shape of the probability density function (pdf), and vector dimensionality itself. In contrast, scalar quantization can utilize effectively only linear dependency and pdf shape. The basic concepts are illustrated by means of simple examples and the theoretical limits of vector quantizer performance are reviewed, based on results from rate-distortion theory. Practical issues relating to quantizer design, implementation, and performance in actual applications are explored. While many of the methods presented are quite general and can be used for the coding of arbitrary signals, this paper focuses primarily on the coding of speech signals and parameters.

961 citations

Journal ArticleDOI
TL;DR: An overview of rate-distortion (R-D) based optimization techniques and their practical application to image and video coding is provided and two popular techniques for resource allocation are introduced, namely, Lagrangian optimization and dynamic programming.
Abstract: In this article we provide an overview of rate-distortion (R-D) based optimization techniques and their practical application to image and video coding. We begin with a short discussion of classical rate-distortion theory and then we show how in many practical coding scenarios, such as in standards-compliant coding environments, resource allocation can be put in an R-D framework. We then introduce two popular techniques for resource allocation, namely, Lagrangian optimization and dynamic programming. After a discussion of these techniques as well as some of their extensions, we conclude with a quick review of literature in these areas citing a number of applications related to image and video compression and transmission.

925 citations

01 Jul 2003
TL;DR: This document describes a profile called "RTP/AVP" for the use of the real-time transport protocol (RTP) and the associated control protocol, RTCP, within audio and video multiparticipant conferences with minimal control.
Abstract: This document describes a profile called "RTP/AVP" for the use of the real-time transport protocol (RTP), version 2, and the associated control protocol, RTCP, within audio and video multiparticipant conferences with minimal control. It provides interpretations of generic fields within the RTP specification suitable for audio and video conferences. In particular, this document defines a set of default mappings from payload type numbers to encodings.

614 citations

Book
01 Feb 1995
TL;DR: A detailed account of the most recently developed digital speech coders designed specifically for use in the evolving communications systems, including an in-depth examination of the important topic of code excited linear prediction (CELP).
Abstract: From the Publisher: A detailed account of the most recently developed digital speech coders designed specifically for use in the evolving communications systems. Discusses the variety of speech coders utilized with such new systems as MBE IMMARSAT-M. Includes an in-depth examination of the important topic of code excited linear prediction (CELP).

453 citations