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Books on the topic 'Soundex algorithm'

Author: Grafiati

Published: 4 June 2025

Last updated: 6 July 2025

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1

Mo, Tsan. Microwave humidity sounder calibration algorithm. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 2004.

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2

Mo, Tsan. Microwave humidity sounder calibration algorithm. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 2004.

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Mo, Tsan. Microwave humidity sounder calibration algorithm. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 2004.

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4

Kacprzyk, Janusz. Music-Inspired Harmony Search Algorithm: Theory and Applications. Springer Berlin Heidelberg, 2009.

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5

Wang, Wenwu. Machine audition: Principles, algorithms, and systems. Information Science Reference, 2010.

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6

Pitre, Richard. A boundary scattering strength extraction algorithm for the analysis of long-range reverberation data. Naval Research Laboratory, 1991.

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7

Garas, John. Adaptive 3D sound systems. Kluwer Academic, 2000.

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8

Nelson, P. A. MINT, the multiple error LMS algorithm, and the design of inverse filters for multi-channel sound reproduction systems. University of Southampton, 1992.

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9

Grecu, Andrei. Musical instrument sound separation: Extracting instruments from musical performances : theory and algorithms. VDM Verlag Dr. Müller, 2008.

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10

1925-, Lee Ding, Sternberg Robert L, Schultz Martin H, and International Association for Mathematics and Computers in Simulation., eds. Computational acoustics: Proceedings of the 1st IMACS Symposium on Computational Acoustics, New Haven, CT, USA, 6-8 August, 1986. North-Holland, 1988.

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11

Miller, Judi A. Lapsley. An algorithm for calculating the essential bandwidth of a discrete spectrum and the essential duration of a discrete time-series. Naval Submarine Medical Research Laboratory, 2001.

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12

McGlothin, Charles C. Ambient sound in the ocean induced by heavy precipitation and the subsequent predictability of rainfall rate. Naval Postgraduate School, 1991.

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13

S, Lyrintzis Anastasios, and United States. National Aeronautics and Space Administration., eds. Development of improved surface integral methods for jet aeroacoustic predictions: Final report, NASA-Langley grant no. NAG-1660. National Aeronautics and Space Administration, 1997.

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14

Oktay, Baysal, and United States. National Aeronautics and Space Administration., eds. Investigation of dispersion-relation-preserving scheme and spectral analysis methods for acoustic waves. National Aeronautics and Space Administration, 1995.

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15

Oktay, Baysal, and United States. National Aeronautics and Space Administration., eds. Investigation of dispersion-relation-preserving scheme and spectral analysis methods for acoustic waves. National Aeronautics and Space Administration, 1995.

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16

Machado, Penousal. Evolutionary and Biologically Inspired Music, Sound, Art and Design: Second International Conference, EvoMUSART 2013, Vienna, Austria, April 3-5, 2013. Proceedings. Springer Berlin Heidelberg, 2013.

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17

Baghai-Ravary, Ladan. Automatic Speech Signal Analysis for Clinical Diagnosis and Assessment of Speech Disorders. Springer New York, 2013.

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18

Schacher, Jan C. Algorithmic Spatialization. Edited by Roger T. Dean and Alex McLean. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190226992.013.12.

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Beginning with a brief historical overview of spatial audio and music practices, this chapter looks at principles of sound spatialization, algorithms for composing and rendering spatial sound and music, and different techniques of spatial source positioning and sound space manipulation. These operations include composing with abstract objects in a sound scene, creating compound sounds using source clusters, altering spatial characteristics by means of spectral sound decomposition, and the manipulation of artificial acoustic spaces. The chapter goes on to discuss practical issues of live spatialization and, through an example piece, the ways a number of different algorithms collaborate in the constitution of a generative audio-visual installation with surround audio and video. Finally, the challenges and pitfalls of using spatialization and some of the common reasons for failure are brought to attention.

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19

Erickson, Kristin. Performing Algorithms. Edited by Roger T. Dean and Alex McLean. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190226992.013.32.

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The chapter considers algorithmic music as the ‘sonification’ of algorithms, a term coined by Carla Scaletti to describe the mapping of numerically represented relations in some domain to relations in an acoustic domain. The chapter looks at the range of ways this concept has been used by the author in composing her works. The chapter identifies isomorphic relationships between algorithms and collaboration, music, and performance, and extends the boundary of the computer to include systems of people and sound. The definition of music and performance is extended to include process, rules, machines, and execution. Examples discussed include performing a bubble sort, pandemic performances (using principles of complex adaptive systems), Mandelbrot music, and M.T.Brain/Telebrain, which send complex algorithmic instructions to multiple performers in real time.

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20

Müller, Meinard. Fundamentals of Music Processing: Audio, Analysis, Algorithms, Applications. Springer, 2016.

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21

Statistically Sound Indicators For Financial Market Prediction: Algorithms in C++. Independently published, 2019.

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22

Auralization Fundamentals Of Acoustics Modelling Simulation Algorithms And Acoustic Virtual Reality. Springer, 2011.

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23

Ďuďák, Juraj. Informačné technológie - úvod do algoritmizácie a základy programovania. SPEKTRUM Publishing, 2024. http://dx.doi.org/10.61544/zoit6119.

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The publication presents the updated and supplemented content of the Information Technology course. The main criterion is to provide a sound basis for teaching algorithmization, the C programming language, and the basics of MATLAB programming. A strong emphasis is placed on the proper definition of the algorithm itself. Based on the developed algorithm, solutions in the C programming language and MATLAB are presented. The content of the course material is designed to be the basis for the courses taught in the upper grades. These subjects require knowledge of basic programming constructs such as constraints, loops, arrays, structures, and similar.

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24

Design of a Heart Sound Extraction Algorithm for an Acoustic-Based Health Monitoring System. Storming Media, 2002.

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25

Vorländer, Michael. Auralization: Fundamentals of Acoustics, Modelling, Simulation, Algorithms and Acoustic Virtual Reality. Springer London, Limited, 2007.

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26

Vorländer, Michael. Auralization: Fundamentals of Acoustics, Modelling, Simulation, Algorithms and Acoustic Virtual Reality. Springer, 2020.

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27

Vorländer, Michael. Auralization: Fundamentals of Acoustics, Modelling, Simulation, Algorithms and Acoustic Virtual Reality. Springer International Publishing AG, 2021.

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28

Auralization: Fundamentals of Acoustics, Modelling, Simulation, Algorithms and Acoustic Virtual Reality (RWTHedition). Springer, 2007.

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29

Fundamentals of Music Processing: Audio, Analysis, Algorithms, Applications. Springer International Publishing AG, 2015.

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30

Fundamentals of Music Processing: Audio, Analysis, Algorithms, Applications. Springer, 2015.

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31

Fink, Robert, Melinda Latour, and Zachary Wallmark, eds. The Relentless Pursuit of Tone. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199985227.001.0001.

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The Relentless Pursuit of Tone: Timbre in Popular Music assembles a wide spectrum of contemporary perspectives on how sound functions in an equally wide array of popular music. With subjects ranging from the twang of country banjos and the sheen of hip-hop strings to the crunch of amplified guitars and the thump of subwoofers on the dance floor, this volume attempts to bridge the gap between timbre, the purely acoustic characteristics of sound waves, and tone, an emergent musical construct that straddles the borderline between the perceptual and the political. The book’s chapters engage with the entire history of popular music as recorded sound, from the 1930s to the present day, under four large categories. The chapters in Part I, “Genre,” ask how sonic signatures define musical identities and publics; Part II, “Voice,” considers the most naturalized musical instrument, the human voice, as racial and gendered signifier, as property or likeness, and as raw material for algorithmic perfection through software; Part III, “Instrument,” tells stories of the way some iconic pop music machines—guitars, strings, synthesizers—got (or lost) their distinctive sounds; and Part IV, “Production,” puts it all together, asking structural questions about what happens in a recording studio, what is produced (sonic cartoons, rockist authenticity, empty space?), and what it all might mean. The book includes a general theoretical introduction by the editors and an afterword by noted popular music scholar Simon Frith.

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32

Computational acoustics: Proceedings of the 1st IMACS Symposium on Computational Acoustics, New Haven, CT, USA, 6-8 August, 1986. Sole distributors for the U.S.A. and Canada, Elsevier Science Pub. Co, 1988.

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33

(Editor), Ding Lee, Robert L. Sternberg (Editor), and Martin H. Schultz (Editor), eds. Computational Acoustics. Elsevier, 1988.

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34

Keislar, Douglas. Computer Music Journal: Language Inventors on the Future of Music Software. MIT Press, 2002.

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35

Keislar, Douglas. Computer Music Journal: Metrical, Harmonic, and Motivic Analysis. MIT Press, 2004.

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36

Keislar, Douglas. Computer Music Journal: In Memoriam Iannis Xenakis. MIT Press, 2002.

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37

Keislar, Douglas. Computer Music Journal: Linux as a Music Platform. MIT Press, 2003.

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38

Computer Music Journal: Sonic Morphing (Volume 27 /3). MIT Press, 2003.

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39

Aronson, David, and Timothy Masters. Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments: Developing Predictive-Model-Based Trading Systems Using TSSB. CreateSpace Independent Publishing Platform, 2013.

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40

Smith, Gary, and Jay Cordes. The Phantom Pattern Problem. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198864165.001.0001.

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Pattern recognition prowess served our ancestors well. However, today we are confronted by a deluge of data that are far more abstract, complicated, and difficult to interpret than were annual seasons and the sounds of predators. The number of possible patterns that can be identified relative to the number that are genuinely useful has grown exponentially—which means that the chances that a discovered pattern is useful is rapidly approaching zero. Coincidental streaks, clusters, and correlations are the norm—not the exception. Our challenge is to overcome our inherited inclination to think that all patterns are meaningful.Computer algorithms can easily identify an essentially unlimited number of phantom patterns and relationships that vanish when confronted with fresh data. The paradox of big data is that the more data we ransack for patterns, the more likely it is that what we find will be worthless. Our challenge is to overcome our inherited inclination to think that all patterns are meaningful.

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41

Schedel, Margaret. Colour is the Keyboard. Edited by Roger T. Dean and Alex McLean. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190226992.013.8.

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This chapter discusses the phenomenon of ‘synaesthesia’, the phenomenon in which a visual perception gives rise to a musical sense-impression, or vice-versa. The chapter covers over one hundred years of artists, composers, and inventors developing sculptures, instruments, and systems to transcode visual data into sonic material. This time frame encompasses mechanical, analogue, digital, and hybrid systems. Most of the algorithmic procedures in these case studies are not reversible; in other words, the visuals cannot be generated from the sound. In many cases the visual aspect is not even meant to be seen as part of the experience, while in others the visual aspect is an equal partner in a synaethestic experience.

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42

Wieser, Renate. Deautomatization of Breakfast Perceptions. Edited by Roger T. Dean and Alex McLean. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190226992.013.28.

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For the author of this chapter, art is a particular way of thinking: it implies the exploring of social and political conditions, not only with the means already provided by academic disciplines, but by finding out new ways to explore, conceptualize, and change them. The chapter describes an art project consisting of an ‘acoustic breakfast’. Sounds of breakfasting were recorded and transformed in real time to make communal interactive music. The author identifies the conflict between artists explaining algorithmic processes to participants and the desire for an informal social situation focussed on eating and drinking. Ideas from literary theorist Shklovsky are used to discuss automatized perceptions and the interest in defamiliarization. Was the acoustic breakfast deautomatizing the computational processes? The chapter discusses the same issue in relation to live coding.

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43

Wannamaker, Robert, Lauren Pratt, and Tashi Wada, eds. James Tenney. Bloomsbury Publishing Plc, 2025. https://doi.org/10.5040/9798765121351.

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This volume collects, for the first time, essential interviews and aesthetic writings from throughout James Tenney's five-decade artistic career. The eminent American-Canadian composer James Tenney (1934–2006) made groundbreaking contributions to sampling culture, digital sound synthesis, algorithmic composition, minimalism, spectral music, music in non-standard tuning systems, contemporary theories of form and harmony, and the consolidation of an American experimental-music tradition. This book documents both his own work and his involvements with influential figures in mid-century American music, film, art, and technology. The writings are accompanied by photographs, artworks, compositional sketches, archival documents, and previously unpublished scores. Appendices supply, for the first time, exhaustive lists of Tenney’s compositions and published writings, as well as performance chronologies that capture his influential contributions to the experimental arts in New York City and elsewhere in the 1960s and 1970s.

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44

Investigation of computational and spectral analysis methods for aeroacoustic wave propagation: Abstract. National Aeronautics and Space Administration, 1995.

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45

Johnson, Colin, Adrian Carballal, and João Correia. Evolutionary and Biologically Inspired Music, Sound, Art and Design: 4th International Conference, EvoMUSART 2015, Copenhagen, Denmark, April 8-10, ... Springer, 2015.

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46

Heuguet, Guillaume. How Music Changed YouTube. Bloomsbury Publishing Inc, 2024. http://dx.doi.org/10.5040/9798765100745.

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How do digital technologies transform music? The answer depends on the lens of one’s analysis: creation, promotion, or the experience of the listener.How Music Changed YouTube shows that the reverse question – How does music transform digital technologies? – is also worth exploring: through reliance on sound recording and music, internet technologies and media are manufactured, transformed, and come to dominate. Guillaume Heuguet’s study situates YouTube in relation to both the internet platform and music industries by unpacking the cultural and technological forms embedded within and observing the practices and values associated with it, from the art of collecting to the accelerated circulation of samples and remixes. Heuguet’s documentary and genealogical work relies on YouTube’s traces in internet archives, its successive interfaces, the blogs of its teams, and a few emblematic channels and videos. Particular attention is paid to the tensions between the promises associated with music algorithms – recommendation system, copyright control, view calculation – and the reality of their operation from a technical and cultural point of view. How Music Changed YouTube shows how, far from responding to an immediate need, YouTube’s editorial and economic model developed over time, how the various fans, artists, labels, lawyers and legislators shaped the site, and how these factors affected its rise as a global media force in the early 21st century.

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47

Carballal, Adrian, Penousal Machado, and James McDermott. Evolutionary and Biologically Inspired Music, Sound, Art and Design: Second International Conference, EvoMUSART 2013, Vienna, Austria, April 3-5, ... Springer, 2013.

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48

Johnson, Colin, Penousal Machado, João Correia, and Vic Ciesielski. Evolutionary and Biologically Inspired Music, Sound, Art and Design: 5th International Conference, EvoMUSART 2016, Porto, Portugal, March 30 -- April 1, 2016, Proceedings. Springer London, Limited, 2016.

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49

Evolutionary and Biologically Inspired Music, Sound, Art and Design: Third European Conference, EvoMUSART 2014, Granada, Spain, April 23-25, 2014, Revised Selected Papers. Springer Berlin / Heidelberg, 2014.

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50

Evolutionary and Biologically Inspired Music, Sound, Art and Design: First International Conference, EvoMUSART 2012, Málaga, Spain, April 11-13, 2012, Proceedings. Springer London, Limited, 2012.

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