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007			cr nn 008mamaa
008			220601s2009 sz | s |||| 0|eng d
020			_a9783031025334
024	7		_a10.1007/978-3-031-02533-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5102.9 _b2009 EB
100	1		_aPadgett, Wayne Thomas, _d1965- _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687638
245	1	0	_aFixed-Point Signal Processing _cby Wayne Padgett, David Anderson
250			_a1st edition 2009
264		1	_aCham _bSpringer International Publishing _c2009
300			_a1 recurso en línea (XI, 121 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Signal Processing _x1932-1694
505	0		_aGetting Started -- DSP Concepts -- Random Processes and Noise -- Fixed Point Numbers -- Quantization Effects: Data and Coefficients -- Quantization Effects - Round-Off Noise and Overflow -- Limit Cycles.
520			_aThis book is intended to fill the gap between the ""ideal precision"" digital signal processing (DSP) that is widely taught, and the limited precision implementation skills that are commonly required in fixed-point processors and field programmable gate arrays (FPGAs). These skills are often neglected at the university level, particularly for undergraduates. We have attempted to create a resource both for a DSP elective course and for the practicing engineer with a need to understand fixed-point implementation. Although we assume a background in DSP, Chapter 2 contains a review of basic theory and Chapter 3 reviews random processes to support the noise model of quantization error. Chapter 4 details the binary arithmetic that underlies fixed-point processors and then introduces fractional format for binary numbers. Chapter 5 covers the noise model for quantization error and the effects of coefficient quantization in filters. Because of the numerical sensitivity of IIR filters, they are used extensively as an example system in both Chapters 5 and 6. Fortunately, the principles of dealing with limited precision can be applied to a wide variety of numerically sensitive systems, not just IIR filters. Chapter 6 discusses the problems of product roundoff error and various methods of scaling to avoid overflow. Chapter 7 discusses limit cycle effects and a few common methods for minimizing them. There are a number of simple exercises integrated into the text to allow you to test your understanding. Answers to the exercises are included in the footnotes. A number of MATLAB examples are provided in the text. They generally assume access to the Fixed-Point Toolbox. If you lack access to this software, consider either purchasing or requesting an evaluation license from The Mathworks. The code listed in the text and other helpful MATLAB code is also available at http://www.morganclaypool.com/page/padgett and http://www.rose-hulman.edu/padgett/fpsp. You will also find MATLAB exercises designed to demonstrate each of the four types of error discussed in Chapters 5 and 6. Simulink examples are also provided on the web site. Table of Contents: Getting Started / DSP Concepts / Random Processes and Noise / Fixed Point Numbers / Quantization Effects: Data and Coefficients / Quantization Effects - Round-Off Noise and Overflow / Limit Cycles.
988			_aSynthesis Collection of Technology_2009
650		7	_2embne _9150609 _aProceso digital de señales
650		7	_2embne _9141102 _aElectrónica digital
700	1		_aAnderson, David Verl, _d1968- _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687639
776	0	8	_iPrinted edition: _z9783031014055
776	0	8	_iPrinted edition: _z9783031036613
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02533-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI