Relevant bibliographies by topics / Adaptive acoustics

Academic literature on the topic 'Adaptive acoustics'

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Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Adaptive acoustics"

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Nixon, Elizabeth, Sue Holland-Crimmin, Brian Lupotsky, James Chan, Jon Curtis, Karen Dobbs, and Zoe Blaxill. "Applications of Adaptive Focused Acoustics to Compound Management." Journal of Biomolecular Screening 14, no. 5 (June 2009): 460–67. http://dx.doi.org/10.1177/1087057109335677.

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Since the introduction of lithotripsy kidney stone therapy, Focused Acoustics and its properties have been thoroughly utilized in medicine and exploration. More recently, Compound Management is exploring its applications and benefits to sample integrity. There are 2 forms of Focused Acoustics: Acoustic Droplet Ejection and Adaptive Focused Acoustics, which work by emitting high-powered acoustic waves through water toward a focused point. This focused power results in noncontact plate-to-plate sample transfer or sample dissolution, respectively. For the purposes of this article, only Adaptive Focused Acoustics will be addressed. Adaptive Focused Acoustics uses high-powered acoustic waves to mix, homogenize, dissolve, and thaw samples. It facilitates transferable samples through noncontact, closed-container, isothermal mixing. Experimental results show significantly reduced mixing times, limited degradation, and ideal use for heat-sensitive compounds. Upon implementation, acoustic dissolution has reduced the number of samples requiring longer mixing times as well as reducing the number impacted by incomplete compound dissolution. It has also helped in increasing the overall sample concentration from 6 to 8 mM to 8 to 10 mM by ensuring complete compound solubilization. The application of Adaptive Focused Acoustics, however, cannot be applied to all Compound Management processes, such as sample thawing and low-volume sample reconstitution. This article will go on to describe the areas where Adaptive Focused Acoustics adds value as well as areas in which it has shown no clear benefit.
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Bartram, J. "Adaptive methods in underwater acoustics." IEEE Journal of Oceanic Engineering 11, no. 4 (October 1986): 487. http://dx.doi.org/10.1109/joe.1986.1145213.

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Lacoume, J. L. "Adaptive methods for underwater acoustics." Signal Processing 13, no. 1 (July 1987): 103–5. http://dx.doi.org/10.1016/0165-1684(87)90118-6.

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Ogoli, David M. "Adaptive thermal comfort factors in classroom acoustics." Journal of the Acoustical Society of America 150, no. 4 (October 2021): A120. http://dx.doi.org/10.1121/10.0007833.

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Mansfield Adams, William. "Adaptive acoustical tomography." Journal of the Acoustical Society of America 79, S1 (May 1986): S16. http://dx.doi.org/10.1121/1.2023088.

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Ma, Kougen, and J. Melcher. "Adaptive Control of Structural Acoustics using Intelligent Structures with Embedded Piezoelectric Patches." Journal of Vibration and Control 9, no. 11 (November 2003): 1285–302. http://dx.doi.org/10.1177/1077546304030676.

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In this paper we focus on the adaptive control of structural acoustics using intelligent structures with embedded piezoelectric (PZT) patches and low cost digital signal processor systems. After a discussion on the adaptive feedforward control scheme, a hybrid adaptive control scheme is proposed, which takes advantage of both feedback control and adaptive feedforward control. The two schemes are realized on a low-cost, small volume, convenient and universal digital signal processing (DSP) board. A carbon fiber reinforced polymer plate with two embedded PZT patches is developed and used in two experiments. The first experiment is adaptive interior noise control using the intelligent plate, in which the adaptive feedforward control scheme is employed. Obvious noise reduction is obtained for constant frequency, swept frequency and varying amplitude harmonic disturbances. The second experiment is adaptive control of sound-induced vibration of the plate, where two embedded PZT patches are used as an actuator and a sensor, respectively, and the hybrid adaptive controller is applied. The full vibration reduction for various harmonic excitations is obtained, verifying the advantage of the hybrid adaptive control. It is demonstrated that active control of structural acoustics can be efficiently achieved by employing intelligent structures, advanced adaptive control schemes and the low-cost DSP board.
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TOPA, M. D., I. MURESAN, B. S. KIREI, and I. HOMANA. "Digital Adaptive Echo-Canceller for Room Acoustics Improvement." Advances in Electrical and Computer Engineering 10, no. 1 (2010): 50–53. http://dx.doi.org/10.4316/aece.2010.01008.

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Zwislocki, Jozef J. "Hot topics in physiological acoustics: The adaptive cochlea." Journal of the Acoustical Society of America 93, no. 4 (April 1993): 2345. http://dx.doi.org/10.1121/1.406261.

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Cray, Benjamin, and Ivars Kirsteins. "A Comparison of Optimal SONAR Array Amplitude Shading Coefficients." Acoustics 1, no. 4 (October 2, 2019): 808–15. http://dx.doi.org/10.3390/acoustics1040047.

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This paper compares two different approaches to deriving shading coefficients (weights) for optimal first order and second order directional sensors (that is; sonobuoys, vectors and dyadic sensors). The first approach is an analytical or a physics-based derivation, involving computations with gradients and linearized momentum; the second is an adaptive minimum variance distortionless response (MVDR) derivation, which finds weights that minimize the cross spectral density (CSD) matrix. The two approaches are shown to be equivalent. In other words, the adaptive MVDR processing procedure does indeed converge to a physics-based solution, without any pre-existing physical knowledge of the behavior of the acoustic field. This suggests that adaptive algorithms innately seek physics-based solutions when these solutions are optimum. The intent of this short communication is not to advocate for one type of adaptive processing method over another. The observation that is presented here is important though, it confirms that at least in an idealized noise field, adaptive processing converges on an optimal set of shading coefficients, similarly derived based on well-established physical acoustics.
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Sharples, Steve D., Matt Clark, and Mike G. Somekh. "All-optical adaptive scanning acoustic microscope." Ultrasonics 41, no. 4 (June 2003): 295–99. http://dx.doi.org/10.1016/s0041-624x(02)00461-4.

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Dissertations / Theses on the topic "Adaptive acoustics"

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Dessalermos, Spyridon. "Undersea acoustic propagation channel estimation." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Jun%5FDessalermos.pdf.

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Thesis (M.S. in Electrical Engineering and M.S. in Applied Physics)--Naval Postgraduate School, June 2005.
Thesis Advisor(s): Joseph Rice, Roberto Cristi. Includes bibliographical references (p. 117-119). Also available online.
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Hermand, Jean-Pierre. "Environmentally-Adaptive Signal Processing in Ocean Acoustics." Doctoral thesis, Universite Libre de Bruxelles, 1993. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/212734.

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Creasy, Miles Austin. "Adaptive Collocated Feedback for Noise Absorption in Acoustic Enclosures." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/45209.

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This thesis focuses on adaptive feedback control for low frequency acoustic energy absorption in acoustic enclosures. The specific application chosen for this work is the reduction of high interior sound pressure levels (SPL) experienced during launch within launch vehicle payload fairings. Two acoustic enclosures are used in the research: the first being a symmetric cylindrical duct and the other being a full scale model of a payload fairing. The symmetric cylindrical duct is used to validate the ability of the adaptive controller to compensate for large changes in the interior acoustical properties. The payload fairing is used to validate that feedback control, for a large geometry, does absorb acoustic energy. The feedback controller studied in this work is positive position feedback (PPF) used in conjunction with high and low pass Butterworth filters. An algorithm is formed from control experiments for setting the filter parameters of the PPF and Butterworth filters from non-adaptive control simulations and tests of the duct and payload fairing. This non-adaptive control shows internal SPL reductions of 2.2 dB in the cylindrical duct for the frequency range from 100 to 500 Hz and internal SPL reductions of 4.2 dB in the full scale fairing model for the frequency range from 50 to 250 Hz. The experimentally formed control algorithm is then used as the basis for an adaptive controller that uses the collocated feedback signal to actively tune the control parameters. The cylindrical duct enclosure with a movable end cap is used to test the adaptation properties of the controller. The movable end cap allows the frequencies of the acoustic modes to vary by more than 20 percent. Experiments show that a 10 percent change in the frequencies of the acoustic modes cause the closed-loop system to go unstable with a non-adaptive controller. The closed-loop system with the adaptive controller maintains stability and reduces the SPL throughout the 20 percent change of the acoustic modes' frequencies with a 2.3 dB SPL reduction before change and a 1.7 dB SPL reduction after the 20 percent change.
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Srinivas, Vivek. "Adaptive, Wave Guiding Acoustic Arrays using Circularly Symmetric Reconfigurable Structures." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587130205893861.

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Fuller, Ryan Michael. "Adaptive Noise Reduction Techniques for Airborne Acoustic Sensors." Wright State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1355361066.

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Freij, G. J. "Enhanced sequential adaptive linear prediction for speech encoding." Thesis, University of Liverpool, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.356268.

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Wong, Lawrence Yik-Lung. "Adaptive system modelling for active attenuation of sound." Thesis, Open University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316967.

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Al-Kindi, Manal Jamil. "Implementation of adaptive noise cancellation in the diving environment." Thesis, University of Strathclyde, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.304949.

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Gillespie, Andrew Fleming Ralph. "The application of adaptive transversal filtering to active noise control." Thesis, London South Bank University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316973.

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John, Ranjit Yohannan. "Adaptive filtering and the identification of tones in broadband noise." Thesis, University of Southampton, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315347.

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Books on the topic "Adaptive acoustics"

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

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

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Adaptive Signal Processing. Springer, 2010.

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

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Book chapters on the topic "Adaptive acoustics"

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Pedersen, Thorkild Find. "Adaptive Processing." In Handbook of Signal Processing in Acoustics, 125–29. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-30441-0_8.

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Owsley, Norman L. "Overview of Adaptive Array Processing." In Adaptive Methods in Underwater Acoustics, 355–74. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1_30.

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Hodgkiss, W. S., and D. Alexandrou. "Applications of Adaptive Array Processing." In Adaptive Methods in Underwater Acoustics, 447–60. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1_40.

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Griffiths, J. W. R. "Twenty Years of Signal Processing." In Adaptive Methods in Underwater Acoustics, 3–12. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1_1.

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Patton, Richard S. "Second Moments of the Pressure Field Near a Smooth Caustic." In Adaptive Methods in Underwater Acoustics, 111–17. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1_10.

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Wasiljeff, Alexander. "Stochastic Systems Theory of the Scattering of Waves from a Random Medium." In Adaptive Methods in Underwater Acoustics, 119–23. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1_11.

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Strasberg, Murray. "Hydrodynamic Flow Noise in Hydrophones." In Adaptive Methods in Underwater Acoustics, 125–43. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1_12.

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Chase, David M. "Wavevector Structure of Turbulent Wall Pressure and its Filtering by Normal Transmission and Spatial Averaging in Sensor Arrays." In Adaptive Methods in Underwater Acoustics, 145–53. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1_13.

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Cook, J. C. "Target Strength and Echo Structure." In Adaptive Methods in Underwater Acoustics, 155–72. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1_14.

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Carter, G. Clifford. "Time Delay Estimation." In Adaptive Methods in Underwater Acoustics, 175–96. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5361-1_15.

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Conference papers on the topic "Adaptive acoustics"

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Zera, Jan. "The Wald Sequential Test as an Alternative Statistics in Staircase Adaptive Procedures." In 2018 Joint Conference - Acoustics. IEEE, 2018. http://dx.doi.org/10.1109/acoustics.2018.8502357.

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Zech, Philipp, Jens Jungblut, Daniel Fritz Ploger, and Stephan Rinderknecht. "Phase-Exact Adaptive Feedforward Control with Reduced Computational Complexity for Modulated Gear Mesh Vibration at 4.7 kHz." In 2018 Joint Conference - Acoustics. IEEE, 2018. http://dx.doi.org/10.1109/acoustics.2018.8502261.

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Wancheng Zhang, Andy W. H. Khong, and Patrick A. Naylor. "Adaptive inverse filtering of room acoustics." In 2008 42nd Asilomar Conference on Signals, Systems and Computers. IEEE, 2008. http://dx.doi.org/10.1109/acssc.2008.5074517.

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Bean, Jacob, Noah H. Schiller, and Chris Fuller. "Full gradient solution to adaptive hybrid control." In 22nd International Congress on Acoustics: Acoustics for the 21st Century. Acoustical Society of America, 2016. http://dx.doi.org/10.1121/2.0000469.

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Yang Juan, Xu Feng, Wei Zhiheng, An Xudong, Liu Jia, Ji Yongqiang, and Wen Tao. "Adaptive Multi-Feature Fusion for underwater diver classification." In 2013 IEEE/OES Acoustics in Underwater Geosciences Symposium (RIO Acoustics). IEEE, 2013. http://dx.doi.org/10.1109/rioacoustics.2013.6684022.

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Karkar, Sami, and Manuel Collet. "Nonreciprocal Acoustics Using Programmable Boundary Conditions: From Boundary Control and Active Metamaterials to the Acoustic Diode." In ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/smasis2017-3797.

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In this communication, we first introduce the concept of programmable boundary conditions, and then use it to design a nonreciprocal acoustic device: an effective, broadband, acoustic diode. Previous works showed that, using sufficiently small transducers, an active acoustic metasurface can be realized: a smart active acoustic skin with tunable acoustic properties. Using distributed control, these properties can be adapted or reconfigured in real-time. Or, it can even depend on the acoustic field itself, allowing for a programming of the (meta)surface properties: a programmable boundary condition. For instance, a partial derivative equation depending on the acoustic quantities can be imposed, in a discretized form, at the surface of such a programmable boundary. This type of non-standard boundary conditions have been shown to provide the necessary basis for nonreciprocal propagation for a plane wave interacting with a boundary with non grazing incidence, ie. for wavevectors that possess a component normal to the boundary. This restriction may appear problematic when the wavevector is then parallel to the boundary, e.g. when dealing with plane waves in a 1D waveguide, as in an acoustic diode. An acoustic diode, or acoustic isolator, is a nonreciprocal device that let acoustic power pass only in one direction, hence breaking the reciprocity of normal acoustic propagation. We propose a new model of acoustic diode, based on active components: a continuous, distributed source inside the domain. However, based on the modeling of parietal sources in ducts, in the low frequency range, we show that the boundary control approach and the distributed domain sources are equivalent. The only difference is that, in the case of the programmable boundary condition, the near-field of the boundary also contains a component normal to the boundary. Hence our acoustic diode can be realized in practice using programmable boundary conditions. Moreover, the acoustic diode is effective on a broad frequency range, since it can work both on the fundamental mode (plane waves) and on higher-order mode of the waveguide.
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Steiger, Kateřina, Pavel Psota, Roman Doleček, David Vápenka, Pavel Mokrý, Jan Václavík, Jakub Nečásek, and Zbyněk Koldovský. "Adaptive acoustic metasurfaces for the active sound field control." In 22nd International Congress on Acoustics: Acoustics for the 21st Century. Acoustical Society of America, 2016. http://dx.doi.org/10.1121/2.0000472.

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Arenas-Garcia, Jeronimo, and Miguel Lazaro-Gredilla. "Tracking performance of adaptively biased adaptive filters." In ICASSP 2011 - 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2011. http://dx.doi.org/10.1109/icassp.2011.5947261.

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Marengo Rodriguez, Fernando A., Sergio A. Castells, and Gonzalo D. Sad. "Perceptual audio coding schemes based on adaptive signal processing tools." In 22nd International Congress on Acoustics: Acoustics for the 21st Century. Acoustical Society of America, 2016. http://dx.doi.org/10.1121/2.0000494.

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Pereselkov, S. A., V. M. Kuzkin, E. S. Kaznacheeva, and S. A. Tkachenko. "ADAPTIVE METHODS OF INTERFEROMETRIC PROCESSING." In The XVII-th Brekhovskikh’s Conference «Ocean Acoustics». Shirshov Institute Publishing House, 2020. http://dx.doi.org/10.29006/978-5-9901449-5-8-44.

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Reports on the topic "Adaptive acoustics"

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Glenn, Scott, Oscar Schofield, and Josh Kohut. Adaptive Sampling in a Research Observatory During the Shallow Water 2006 Acoustics Experiment. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada573267.

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Cheung, Mei Y. Autonomous Adaptive Acoustic Relay Positioning. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada597425.

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Schmidt, Henrik, John J. Leonard, and David Battle. GOATS 2005: Integrated, Adaptive Autonomous Acoustic Sensing Systems. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada611929.

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Cross, L. E. Materials for Adaptive Structural Acoustic Control. Volume 6. Fort Belvoir, VA: Defense Technical Information Center, March 1996. http://dx.doi.org/10.21236/ada310984.

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Schmidt, Henrik, John J. Leonard, and David Battle. GOATS 2005 Integrated, Adaptive Autonomous Acoustic Sensing Systems. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada569082.

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Neumann, Peter, and Gregory Muncill. Using Adaptive Simulated Annealing to Estimate Ocean Bottom Acoustic Properties from Acoustic Data. Fort Belvoir, VA: Defense Technical Information Center, May 2000. http://dx.doi.org/10.21236/ada377982.

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Kuperman, W. A. Self-Adaptive Methods to Characterize Bio-Acoustic Scattering and Propagation. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada574947.

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Hatanaka, M., and J. Matsumoto. RTP Payload Format for the Adaptive TRansform Acoustic Coding (ATRAC) Family. RFC Editor, July 2009. http://dx.doi.org/10.17487/rfc5584.

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Beaujean, Pierre-Philippe, and Steven Schock. Smart Acoustic Network Using Combined Fsk-Psk, Adaptive Beamforming and Equalization. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada629527.

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LeBlanc, Lester R., and Pierre-Philippe J. Beaujean. Smart Acoustic Network Using Combined FSK-PSK, Adaptive, Beamforming and Equalization. Fort Belvoir, VA: Defense Technical Information Center, August 2001. http://dx.doi.org/10.21236/ada628285.

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