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Books on the topic 'Adaptive acoustics'

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Author: Grafiati

Published: 30 May 2022

Last updated: 31 May 2022

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1

1937-, Urban Heinz G., and North Atlantic Treaty Organization. Scientific Affairs Division., eds. Adaptive methods in underwater acoustics. Dordrecht: D. Reidel Pub. Co., 1985.

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2

NATO Advanced Study Instituteon Adaptive Methods in Underwater Acoustics (1984 Luneburg, Germany). Adaptive methods in underwater acoustics. Dordrecht: Reidel published in Cooperation with NATO Scientific Affairs Division, 1985.

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3

Urban, Heinz G., ed. Adaptive Methods in Underwater Acoustics. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1.

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4

Schobben, Daniel W. E. Real-time Adaptive Concepts in Acoustics. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0812-9.

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5

Schobben, Daniel W. E. Real-time Adaptive Concepts in Acoustics: Blind Signal Separation and Multichannel Echo Cancellation. Dordrecht: Springer Netherlands, 2001.

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6

Helwani, Karim. Adaptive Identification of Acoustic Multichannel Systems Using Sparse Representations. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08954-6.

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7

Widrow, Bernard. Adaptive inverse control: A signal processing approach. Piscataway, NJ: IEEE Press, 2008.

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8

Urban, H. G. Adaptive Methods in Underwater Acoustics. Springer, 2011.

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9

Adaptive Signal Processing. Springer, 2010.

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10

Adaptive Feedforward Control Of Low Frequency Interior Noise. Springer, 2011.

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11

Real-Time Adaptive Concepts in Acoustics: Blind Signal Separation and Multichannel Echo Cancellation. Springer, 2001.

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12

Kletschkowski, Thomas. Adaptive Feed-Forward Control of Low Frequency Interior Noise. Springer, 2016.

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13

Kletschkowski, Thomas. Adaptive Feed-Forward Control of Low Frequency Interior Noise. Springer, 2011.

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14

Jacob, Benesty, ed. Advances in network and acoustic echo cancellation / J. Benesty ... [et al.]. New York: Springer, 2001.

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15

Benesty, Jacob. Advances in Network and Acoustic Echo Cancellation (Digital Signal Processing). Springer, 2001.

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16

Helwani, Karim. Adaptive Identification of Acoustic Multichannel Systems Using Sparse Representations. Springer, 2016.

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17

Helwani, Karim. Adaptive Identification of Acoustic Multichannel Systems Using Sparse Representations. Springer, 2014.

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18

Walach, Eugene, and Bernard Widrow. Adaptive Inverse Control, Reissue Edition: A Signal Processing Approach. Wiley-IEEE Press, 2007.

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19

L, Gay Steven, and Benesty Jacob, eds. Acoustic signal processing for telecommunication. Boston: Kluwer Academic, 2000.

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20

(Editor), Steven L. Gay, and Jacob Benesty (Editor), eds. Acoustic Signal Processing for Telecommunication (The Springer International Series in Engineering and Computer Science). Springer, 2000.

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21

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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22

De Souza, Jonathan. Sounding Actions. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190271114.003.0003.

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When a musical instrument converts energy into sound, it makes aspects of the player’s action audible. This chapter analyzes this action-sound coupling in various instruments, drawing on ecological acoustics, organology, and cybernetics. It introduces a distinction between two aspects of sound production—“activation” and “control”—either of which may come from the player or the instrument. Pipe organs, for example, are activated by nonhuman power sources, though the pitches are controlled by the organist. Barrel organs, by contrast, are activated by human energy, but the pitches are preprogrammed. Instrumental sound production also involves distinctive combinations of sonic, visual, and tactile feedback. Moreover, by adapting Merleau-Ponty’s work on the body schema, this theory of action-sound coupling accounts for the feeling, often reported by performers, that an instrument is an extension of the body.

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