The Experts below are selected from a list of 11976 Experts worldwide ranked by ideXlab platform

George A Constantinides - One of the best experts on this subject based on the ideXlab platform.

  • error modelling of dual fixed point arithmetic and its application in field programmable logic
    Field-Programmable Logic and Applications, 2005
    Co-Authors: Chun Te Ewe, P V K Cheung, George A Constantinides
    Abstract:

    Dual FiXed-point (DFX) is a new data representation which is an efficient compromise between fixed-point and floating-point representations. DFX has an implementation complexity similar to that of a fixed-point system with the improved dynamic range capability of a floating-point system. Automating the process of DFX scaling optimisation requires the knowledge of its truncation/rounding noise properties. This paper presents truncation and rounding error models for DFX arithmetic as traditional error models do not apply to DFX. The models were tested on a 159-tap FIR filter and the benefits of using DFX over floating-point are demonstrated with implementations on a Xilinx Virtex II Pro.

  • FPL - Dual Fixed-point: An Efficient Alternative to floating-point Computation
    Field Programmable Logic and Application, 2004
    Co-Authors: Peter Y. K. Cheung, George A Constantinides
    Abstract:

    This paper presents a new data representation known as Dual FiXed-point (DFX), which employs a single bit exponent to select two different fixed-point scalings. DFX provides a compromise between conventional fixed-point and floating-point representations. It has the implementation complexity similar to that of a fixed-point system together with the improved dynamic range offered by a floating-point system. The benefit of using DFX over both fixed-point and floating-point is demonstrated with an IIR filter implementation on a Xilinx Virtex II FPGA.

  • dual fixed point an efficient alternative to floating point computation
    Lecture Notes in Computer Science, 2004
    Co-Authors: Peter Y. K. Cheung, George A Constantinides
    Abstract:

    This paper presents a new data representation known as Dual FiXed-point (DFX), which employs a single bit exponent to select two different fixed-point scalings. DFX provides a compromise between conventional fixed-point and floating-point representations. It has the implementation complexity similar to that of a fixed-point system together with the improved dynamic range offered by a floating-point system. The benefit of using DFX over both fixed-point and floating-point is demonstrated with an IIR filter implementation on a Xilinx Virtex II FPGA.

Peter Y. K. Cheung - One of the best experts on this subject based on the ideXlab platform.

  • FPL - Dual Fixed-point: An Efficient Alternative to floating-point Computation
    Field Programmable Logic and Application, 2004
    Co-Authors: Peter Y. K. Cheung, George A Constantinides
    Abstract:

    This paper presents a new data representation known as Dual FiXed-point (DFX), which employs a single bit exponent to select two different fixed-point scalings. DFX provides a compromise between conventional fixed-point and floating-point representations. It has the implementation complexity similar to that of a fixed-point system together with the improved dynamic range offered by a floating-point system. The benefit of using DFX over both fixed-point and floating-point is demonstrated with an IIR filter implementation on a Xilinx Virtex II FPGA.

  • dual fixed point an efficient alternative to floating point computation
    Lecture Notes in Computer Science, 2004
    Co-Authors: Peter Y. K. Cheung, George A Constantinides
    Abstract:

    This paper presents a new data representation known as Dual FiXed-point (DFX), which employs a single bit exponent to select two different fixed-point scalings. DFX provides a compromise between conventional fixed-point and floating-point representations. It has the implementation complexity similar to that of a fixed-point system together with the improved dynamic range offered by a floating-point system. The benefit of using DFX over both fixed-point and floating-point is demonstrated with an IIR filter implementation on a Xilinx Virtex II FPGA.

Burt Holland - One of the best experts on this subject based on the ideXlab platform.

  • Statistical Analysis and Data Display: An Intermediate Course with Examples in R
    2015
    Co-Authors: Richard M. Heiberger, Burt Holland
    Abstract:

    This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data-showing code, graphics, and accompanying tabular listings-for all the methods they cover. They emphasize how to construct and interpret graphs. They discuss principles of graphical design. They identify situations where visual impressions from graphs may need confirmation from traditional tabular results. All chapters have exercises. The authors provide and discuss R functions for all the new graphical display formats. All graphs and tabular output in the book were constructed using these functions. Complete R scripts for all examples and figures are provided for readers to use as models for their own analyses. This book can serve as a standalone text for statistics majors at the master's level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays. The Second Edition features graphs that are completely redrawn using the more powerful graphics infrastructure provided by R's lattice package. There are new sections in several of the chapters, revised sections in all chapters and several completely new appendices. New graphical material includes: * an expanded chapter on graphics * a section on graphing Likert Scale Data to build on the importance of rating scales in fields from population studies to psychometrics * a discussion on design of graphics that will work for readers with color-deficient vision * an expanded discussion on the design of multi-panel graphics * expanded and new sections in the discrete bivariate statistics capter on the use of mosaic plots for contingency tables including the nx2x2 tables for which the Mantel-Haenszel-Cochran test is appropriate * an interactive (using the shiny package) presentation of the graphics for the normal and t-tables that is introduced early and used in many chapters The new appendices include discussions of R, the HH package designed for R (the material in the HH package was distributed as a set of standalone functions with the First Edition of this book), the R Commander package, the RExcel system, the shiny package, and a minimal discussion on writing R packages. There is a new appendix on computational precision illustrating and explaining the FAQ (Frequently Asked Questions) about the differences between the familiar real number system and the less-familiar floating point system used in computers. The probability distributions appendix has been expanded to include more distributions (all the distributions in base R) and to include graphs of each. The editing appendix from the First Edition has been split into four expanded appendices-on working style, writing style, use of a powerful editor, and use of LaTeX for document preparation.

  • Statistical Analysis and Data Display
    Springer Texts in Statistics, 2015
    Co-Authors: Richard M. Heiberger, Burt Holland
    Abstract:

    This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying tabular listings—for all the methods they cover. They emphasize how to construct and interpret graphs. They discuss principles of graphical design. They identify situations where visual impressions from graphs may need confirmation from traditional tabular results. All chapters have exercises. The authors provide and discuss R functions for all the new graphical display formats. All graphs and tabular output in the book were constructed using these functions. Complete R scripts for all examples and figures are provided for readers to use as models for their own analyses. This book can serve as a standalone text for statistics majors at the master’s level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays. The Second Edition features graphs that are completely redrawn using the more powerful graphics infrastructure provided by R's lattice package. There are new sections in several of the chapters, revised sections in all chapters and several completely new appendices. New graphical material includes: • an expanded chapter on graphics; • a section on graphing Likert Scale Data to build on the importance of rating scales in fields from population studies to psychometrics; • a discussion on design of graphics that will work for readers with color-deficient vision; • an expanded discussion on the design of multi-panel graphics; • expanded and new sections in the discrete bivariate statistics chapter on the use of mosaic plots for contingency tables including the n×2×2 tables for which the Mantel–Haenszel–Cochran test is appropriate; • an interactive (using the shiny package) presentation of the graphics for the normal and t-tables that is introduced early and used in many chapters. The new appendices include discussions of R, the HH package designed for R (the material in the HH package was distributed as a set of standalone functions with the First Edition of this book), the R Commander package, the RExcel system, the shiny package, and a minimal discussion on writing R packages. There is a new appendix on computational precision illustrating and explaining the FAQ (Frequently Asked Questions) about the differences between the familiar real number system and the less-familiar floating point system used in computers. The probability distributions appendix has been expanded to include more distributions (all the distributions in base R) and to include graphs of each. The editing appendix from the First Edition has been split into four expanded appendices—on working style, writing style, use of a powerful editor, and use of LaTeX for document preparation

Richard M. Heiberger - One of the best experts on this subject based on the ideXlab platform.

  • Statistical Analysis and Data Display: An Intermediate Course with Examples in R
    2015
    Co-Authors: Richard M. Heiberger, Burt Holland
    Abstract:

    This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data-showing code, graphics, and accompanying tabular listings-for all the methods they cover. They emphasize how to construct and interpret graphs. They discuss principles of graphical design. They identify situations where visual impressions from graphs may need confirmation from traditional tabular results. All chapters have exercises. The authors provide and discuss R functions for all the new graphical display formats. All graphs and tabular output in the book were constructed using these functions. Complete R scripts for all examples and figures are provided for readers to use as models for their own analyses. This book can serve as a standalone text for statistics majors at the master's level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays. The Second Edition features graphs that are completely redrawn using the more powerful graphics infrastructure provided by R's lattice package. There are new sections in several of the chapters, revised sections in all chapters and several completely new appendices. New graphical material includes: * an expanded chapter on graphics * a section on graphing Likert Scale Data to build on the importance of rating scales in fields from population studies to psychometrics * a discussion on design of graphics that will work for readers with color-deficient vision * an expanded discussion on the design of multi-panel graphics * expanded and new sections in the discrete bivariate statistics capter on the use of mosaic plots for contingency tables including the nx2x2 tables for which the Mantel-Haenszel-Cochran test is appropriate * an interactive (using the shiny package) presentation of the graphics for the normal and t-tables that is introduced early and used in many chapters The new appendices include discussions of R, the HH package designed for R (the material in the HH package was distributed as a set of standalone functions with the First Edition of this book), the R Commander package, the RExcel system, the shiny package, and a minimal discussion on writing R packages. There is a new appendix on computational precision illustrating and explaining the FAQ (Frequently Asked Questions) about the differences between the familiar real number system and the less-familiar floating point system used in computers. The probability distributions appendix has been expanded to include more distributions (all the distributions in base R) and to include graphs of each. The editing appendix from the First Edition has been split into four expanded appendices-on working style, writing style, use of a powerful editor, and use of LaTeX for document preparation.

  • Statistical Analysis and Data Display
    Springer Texts in Statistics, 2015
    Co-Authors: Richard M. Heiberger, Burt Holland
    Abstract:

    This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying tabular listings—for all the methods they cover. They emphasize how to construct and interpret graphs. They discuss principles of graphical design. They identify situations where visual impressions from graphs may need confirmation from traditional tabular results. All chapters have exercises. The authors provide and discuss R functions for all the new graphical display formats. All graphs and tabular output in the book were constructed using these functions. Complete R scripts for all examples and figures are provided for readers to use as models for their own analyses. This book can serve as a standalone text for statistics majors at the master’s level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays. The Second Edition features graphs that are completely redrawn using the more powerful graphics infrastructure provided by R's lattice package. There are new sections in several of the chapters, revised sections in all chapters and several completely new appendices. New graphical material includes: • an expanded chapter on graphics; • a section on graphing Likert Scale Data to build on the importance of rating scales in fields from population studies to psychometrics; • a discussion on design of graphics that will work for readers with color-deficient vision; • an expanded discussion on the design of multi-panel graphics; • expanded and new sections in the discrete bivariate statistics chapter on the use of mosaic plots for contingency tables including the n×2×2 tables for which the Mantel–Haenszel–Cochran test is appropriate; • an interactive (using the shiny package) presentation of the graphics for the normal and t-tables that is introduced early and used in many chapters. The new appendices include discussions of R, the HH package designed for R (the material in the HH package was distributed as a set of standalone functions with the First Edition of this book), the R Commander package, the RExcel system, the shiny package, and a minimal discussion on writing R packages. There is a new appendix on computational precision illustrating and explaining the FAQ (Frequently Asked Questions) about the differences between the familiar real number system and the less-familiar floating point system used in computers. The probability distributions appendix has been expanded to include more distributions (all the distributions in base R) and to include graphs of each. The editing appendix from the First Edition has been split into four expanded appendices—on working style, writing style, use of a powerful editor, and use of LaTeX for document preparation

Marc Daumas - One of the best experts on this subject based on the ideXlab platform.

  • Properties of the subtraction valid for any floating point system
    2002
    Co-Authors: Sylvie Boldo, Marc Daumas
    Abstract:

    We start in this text with a very generic definition of floating point systems. We show that just a few very natural necessary conditions are sufficient to focus down to two classes of implemented floating point arithmetic. Later, we prove that, for all the existing implementations, high level properties such as Sterbenz's theorem are satisfied. We finish this text by focusing on the differences between an IEEE-754 compatible unit and Texas Instrument TMS/SMJ 320C3x digital signal processing circuit that is recommended for avionics and military applications. The results presented in this text have been validated by the Coq automatic proof checker to build confidence for later implementations in critical systems such as an aircraft flight control primary or secondary computer.