Relevant bibliographies by topics / Acoustic equalization

Academic literature on the topic 'Acoustic equalization'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Acoustic equalization.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Acoustic equalization"

1

Song, Hee-Chun. "Bidirectional equalization for underwater acoustic communications." Journal of the Acoustical Society of America 132, no. 3 (September 2012): 2016. http://dx.doi.org/10.1121/1.4755462.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Isvan, Osman Kemal. "DUAL MODE EARPHONE WITH ACOUSTIC EQUALIZATION." Journal of the Acoustical Society of America 132, no. 2 (2012): 1238. http://dx.doi.org/10.1121/1.4742634.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Song, H. C. "Bidirectional equalization for underwater acoustic communication." Journal of the Acoustical Society of America 131, no. 4 (April 2012): EL342—EL347. http://dx.doi.org/10.1121/1.3695075.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Liu, Yan, and Yuan Min Li. "Novel DFE for Underwater Acoustic Channels." Advanced Materials Research 760-762 (September 2013): 691–94. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.691.

Full text
Abstract:
In underwater acoustic communication systems, the channel equalization community has recently given much attention to decision feedback equalization (DFE). It is because that the DFE offers intersymbol interference (ISI) cancellation with reduced noise enhancement. However, its key algorithm such as constant modulus algorithm (CMA) has moderate convergence rate and steady-state mean square error (MSE), which is not sufficient for the receive system of communication. So a new cost function is defined and then a novel DFE based on such cost function is proposed. The efficiency of the proposed DFE is proved by computer simulations.
APA, Harvard, Vancouver, ISO, and other styles
5

Sun, Lin, Mei Wang, Guoheng Zhang, Haisen Li, and Lan Huang. "Filtered Multitone Modulation Underwater Acoustic Communications Using Low-Complexity Channel-Estimation-Based MMSE Turbo Equalization." Sensors 19, no. 12 (June 17, 2019): 2714. http://dx.doi.org/10.3390/s19122714.

Full text
Abstract:
Filtered multitone (FMT) modulation divides the communication band into several subbands to shorten the span of symbols affected by multipath in underwater acoustic (UWA) communications. However, there is still intersymbol interference (ISI) in each subband of FMT modulation degrading communication performance. Therefore, ISI suppression techniques must be applied to FMT modulation UWA communications. The suppression performance of traditional adaptive equalization methods often exploited in FMT modulation UWA communications is limited when the effect of ISI spans tens of symbols or large constellation sizes are used. Turbo equalization consisting of adaptive equalization and channel decoding can improve equalization performance through information exchanging and iterative processes. To overcome the shortcoming of traditional minimum mean square error (MMSE) equalization and effectively suppress the ISI with relatively low computation complexity, an FMT modulation UWA communication using low-complexity channel-estimation-based (CE-based) MMSE turbo equalization is proposed in this paper. In the proposed method, turbo equalization is first exploited to suppress the ISI in FMT modulation UWA communications, and the equalizer coefficients of turbo equalization are adjusted using the low-complexity CE-based MMSE algorithm. The proposed method is analyzed in theory and verified by simulation analysis and real data collected in the experiment carried out in a pool with multipath propagation. The results demonstrate that the proposed method can achieve better communication performance with a higher bit rate than the FMT modulation UWA communication using traditional MMSE adaptive equalization.
APA, Harvard, Vancouver, ISO, and other styles
6

Xiao, Ying, and Rui Ruan. "CMA Blind Equalization with Quasi-Newton Algorithm in Underwater Acoustic Channels Based on Simplified Cost Function." Advanced Materials Research 989-994 (July 2014): 1865–68. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.1865.

Full text
Abstract:
The CMA cost function is simplified to meet the second norm form, and a new CMA blind equalization based on quasi-newton algorithm is proposed. Since the CMA cost function does not meet the second norm form, it is difficult to use quasi-newton algorithm to update the blind equalizer directly based on the cost function of CMA. If the cost function is simplified to meet the second norm form, it can use quasi-newton algorithm to update the blind equalizer directly. Thus, the convergence rate and convergence precision of CMA blind equalization can be improved effectively. Simulation results under the acoustic channels show that CMA blind equalization with quasi-newton algorithm based on the simplified cost function has faster convergence rate and less steady state residual error, which has practical value in the blind equalization of fast time-varying underwater acoustic channels
APA, Harvard, Vancouver, ISO, and other styles
7

Proakis, J. G. "Adaptive equalization techniques for acoustic telemetry channels." IEEE Journal of Oceanic Engineering 16, no. 1 (1991): 21–31. http://dx.doi.org/10.1109/48.64882.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Pelekanakis, Konstantinos, and Mandar Chitre. "Robust Equalization of Mobile Underwater Acoustic Channels." IEEE Journal of Oceanic Engineering 40, no. 4 (October 2015): 775–84. http://dx.doi.org/10.1109/joe.2015.2469895.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Zheng, Yahong Rosa, Jingxian Wu, and Chengshan Xiao. "Turbo equalization for single-carrier underwater acoustic communications." IEEE Communications Magazine 53, no. 11 (November 2015): 79–87. http://dx.doi.org/10.1109/mcom.2015.7321975.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Chen, Xi, Scott D. Sommerfeldt, and Timothy W. Leishman. "An adaptive equalization scheme using acoustic energy density." Journal of the Acoustical Society of America 115, no. 5 (May 2004): 2612. http://dx.doi.org/10.1121/1.4784781.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Acoustic equalization"

1

Zhang, Wancheng. "Robust equalization of multichannel acoustic systems." Thesis, Imperial College London, 2010. http://hdl.handle.net/10044/1/5882.

Full text
Abstract:
In most real-world acoustical scenarios, speech signals captured by distant microphones from a source are reverberated due to multipath propagation, and the reverberation may impair speech intelligibility. Speech dereverberation can be achieved by equalizing the channels from the source to microphones. Equalization systems can be computed using estimates of multichannel acoustic impulse responses. However, the estimates obtained from system identification always include errors; the fact that an equalization system is able to equalize the estimated multichannel acoustic system does not mean that it is able to equalize the true system. The objective of this thesis is to propose and investigate robust equalization methods for multichannel acoustic systems in the presence of system identification errors. Equalization systems can be computed using the multiple-input/output inverse theorem or multichannel least-squares method. However, equalization systems obtained from these methods are very sensitive to system identification errors. A study of the multichannel least-squares method with respect to two classes of characteristic channel zeros is conducted. Accordingly, a relaxed multichannel least- squares method is proposed. Channel shortening in connection with the multiple- input/output inverse theorem and the relaxed multichannel least-squares method is discussed. Two algorithms taking into account the system identification errors are developed. Firstly, an optimally-stopped weighted conjugate gradient algorithm is proposed. A conjugate gradient iterative method is employed to compute the equalization system. The iteration process is stopped optimally with respect to system identification errors. Secondly, a system-identification-error-robust equalization method exploring the use of error models is presented, which incorporates system identification error models in the weighted multichannel least-squares formulation.
APA, Harvard, Vancouver, ISO, and other styles
2

Yellepeddi, Atulya. "Direct-form adaptive equalization for underwater acoustic communication." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1912/5281.

Full text
Abstract:
Thesis (S.M.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 139-143).
Adaptive equalization is an important aspect of communication systems in various environments. It is particularly important in underwater acoustic communication systems, as the channel has a long delay spread and is subject to the effects of time- varying multipath fading and Doppler spreading. The design of the adaptation algorithm has a profound influence on the performance of the system. In this thesis, we explore this aspect of the system. The emphasis of the work presented is on applying concepts from inference and decision theory and information theory to provide an approach to deriving and analyzing adaptation algorithms. Limited work has been done so far on rigorously devising adaptation algorithms to suit a particular situation, and the aim of this thesis is to concretize such efforts and possibly to provide a mathematical basis for expanding it to other applications. We derive an algorithm for the adaptation of the coefficients of an equalizer when the receiver has limited or no information about the transmitted symbols, which we term the Soft-Decision Directed Recursive Least Squares algorithm. We will demonstrate connections between the Expectation-Maximization (EM) algorithm and the Recursive Least Squares algorithm, and show how to derive a computationally efficient, purely recursive algorithm from the optimal EM algorithm. Then, we use our understanding of Markov processes to analyze the performance of the RLS algorithm in hard-decision directed mode, as well as of the Soft-Decision Directed RLS algorithm. We demonstrate scenarios in which the adaptation procedures fail catastrophically, and discuss why this happens. The lessons from the analysis guide us on the choice of models for the adaptation procedure. We then demonstrate how to use the algorithm derived in a practical system for underwater communication using turbo equalization. As the algorithm naturally incorporates soft information into the adaptation process, it becomes easy to fit it into a turbo equalization framework. We thus provide an instance of how to use the information of a turbo equalizer in an adaptation procedure, which has not been very well explored in the past. Experimental data is used to prove the value of the algorithm in a practical context.
by Atulya Yellepeddi.
S.M.
APA, Harvard, Vancouver, ISO, and other styles
3

Talantzis, Fotios. "Equalization and source separation techniques in acoustic reverberant environments." Thesis, Imperial College London, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428487.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Sifferlen, James F. "Iterative equalization and decoding applied to underwater acoustic communication." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3331419.

Full text
Abstract:
Thesis (Ph. D.)--University of California, San Diego, 2008.
Title from first page of PDF file (viewed Dec. 16, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 131-134).
APA, Harvard, Vancouver, ISO, and other styles
5

Allander, Martin. "Channel Equalization Using Machine Learning for Underwater Acoustic Communications." Thesis, Linköpings universitet, Kommunikationssystem, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166643.

Full text
Abstract:
Wireless underwater acoustic (UWA) communications is a developing field with various applications. The underwater acoustic communication channel is very special and its behavior is environment-dependent. The UWA channel is characterized by low available bandwidth, and severe motion-introduced Doppler effectcompared to wireless radio communication. Recent literature suggests that machine learning (ML)-based channel estimation and equalization offer benefits overtraditional techniques (a decision feedback equalizer), in UWA communications. ML can be advantageous due to the difficultly in designing algorithms for UWA communication, as finding general channel models have proven to be difficult. This study aims to explore if ML-based channel estimation and equalization as a part of a sophisticated physical layer structure can offer improved performance. In the study, supervised ML using a deep neural network and a recurrent neural network will be utilized to improve the bit error rate. A channel simulator with environment-specific input is used to study a wide range of channels. The simulations are utilized to study in which environments ML should be tested. It is shown that in highly time-varying channels, ML outperforms traditional techniques if trained with prior information of the channel. However, utilizing ML without prior information of the channel yielded no improvement of the performance.
APA, Harvard, Vancouver, ISO, and other styles
6

Kuchler, Ryan J. "Comparison of channel equalization filtering techniquies in underwater acoustic communications." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02Jun%5FKuchler.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Puikkonen, Panu Tapani. "Development of an Adaptive Equalization Algorithm Using Acoustic Energy Density." BYU ScholarsArchive, 2009. https://scholarsarchive.byu.edu/etd/1686.

Full text
Abstract:
Sound pressure equalization of audio signals using digital signal processors has been a subject of ongoing study for many years. The traditional approach is to equalize sound at a point in a listening environment, but because of its specific dependence on the room frequency response between a source and receiver position, this equalization generally causes the spectral response to worsen significantly at other locations in the room. This work presents both a time-invariant and a time-varying implementation of an adaptive acoustic energy density equalization filter for a one-dimensional sound field. Energy density equalization addresses the aforementioned challenge and others that relate to sound equalization. The theory and real-time implementation of time-invariant sound pressure and energy density equalizers designed using the least-squares method are presented, and their performances are compared. An implementation of a time-varying energy density equalizer is also presented. Time-invariant equalization results based on real-time measurements in a plane-wave tube are presented. A sound pressure equalizer results in a nearly flat spectral magnitude at the point of equalization. However, it causes the frequencies corresponding to spatial nulls at that point to be undesirably boosted elsewhere in the sound field, where those nulls do not exist at the same frequencies. An energy density equalization filter identifies and compensates for all resonances and other global spectral effects of the tube and loudspeaker. It does not attempt to equalize the spatially varying frequency nulls caused by local pressure nodes at the point of equalization. An implementation of a time-varying energy density equalizer is also presented. This method uses the filtered-x filter update to adjust the filter coefficients in real-time to adapt to changes in the sound field. Convergence of the filter over time is demonstrated as the closed end of the tube is opened, then closed once again. Thus, the research results demonstrate that an acoustic energy density filter can be used to time-adaptively equalize global spectral anomalies of a loudspeaker and a one-dimensional sound field.
APA, Harvard, Vancouver, ISO, and other styles
8

Lewis, Matthew Robert S. M. Massachusetts Institute of Technology. "Evaluation of vector sensors for adaptive equalization in underwater acoustic communication." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/93793.

Full text
Abstract:
Thesis: S.M., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 123-125).
Underwater acoustic communication is an extremely complex field that faces many challenges due to the time-varying nature of the ocean environment. Vector sensors are a proven technology that when utilizing their directional sensing capabilities allows us to minimize the effect of interfering noise sources. A traditional pressure sensor array has been the standard for years but suffers at degraded signal to noise ratios (SNR) and requires maneuvers or a lengthly array aperture to direction find. This thesis explores the effect of utilizing a vector sensor array to steer to the direction of signal arrival and the effect it has on equalization of the signal at degraded SNRs. It was demonstrated that utilizing a single vector sensor we were able steer to the direction of arrival and improve the ability of an equalizer to determine the transmitted signal. This improvement was most prominent when the SNR was degraded to levels of 0 and 10 dB where the performance of the vector sensor outperformed that of the pressure sensor in nearly 100% of cases. Finally, this performance improvement occurred with a savings in computational expense.
by Matthew Robert Lewis.
S.M.
APA, Harvard, Vancouver, ISO, and other styles
9

Kuchler, Ryan J. "Comparison of channel equalization filtering techniques in underwater acoustic communications." Thesis, Monterey California. Naval Postgraduate School, 2002. http://hdl.handle.net/10945/5887.

Full text
Abstract:
In this thesis, underwater acoustic communications signal processing techniques, which are used to equalize the distortional effects associated with the ocean as a communications channel, are investigated for a shallow water ocean environment. The majority of current signal processing techniques employ a Finite Impulse Response (FIR) filter. Three equalization filters were investigated and presented as alternatives; they were the passive time-reversed filter, the inverse filter, and the Infinite Impulse Response (IIR) filter. The main advantage of the passive time-reversed filter and the inverse filter is simplicity of design. Bit error rates for the time-reversed filter were consistently around 10-1 and those for the inverse filter were greater than 10-1. However, inability of the passive time-reversed filter to completely eliminate multipath components and the ill-conditioned nature of the inverse filter made it difficult to achieve Probability of Error results below 10-1. Research into the development of an array receiver using a time-reversed filter should improve calculated bit error rates. Simulations of the IIR filter were conducted with limited success. The main advantage of an IIR filter is that fewer parameters are required in the design of the filter. However, the potential for instability in the filter is a significant limitation. Probability of Error results were found to be on the order of those for current FIR filters at close ranges. Unfortunately, instability issues arose for receivers as range from the source increased. This research on the IIR filter is still in the embryonic stage, whereas research using FIR filters is relatively highly developed. Further research is needed to address the issue of instability in IIR filters in order to make them an effective signal processing technique employable in underwater acoustic communications.
APA, Harvard, Vancouver, ISO, and other styles
10

Puikkonen, Panu. "Development of an adaptive equalization algorithm using acoustic energy density /." Diss., CLICK HERE for online access, 2009. http://contentdm.lib.byu.edu/ETD/image/etd2899.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Acoustic equalization"

1

Comparison of Channel Equalization Filtering Techniques in Underwater Acoustic Communications. Storming Media, 2002.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Acoustic equalization"

1

Barroso, Victor A. N., and Carlos A. C. Belo. "A Model Based Equalization Structure for Underwater Communications." In Acoustic Signal Processing for Ocean Exploration, 601–6. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1604-6_56.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Liu, Zhiyong, Yinyin Wang, and Fan Bai. "Variable Tap-Length Blind Equalization for Underwater Acoustic Communication." In Machine Learning and Intelligent Communications, 127–35. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00557-3_13.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Ke, Miao, Zhiyong Liu, and Xuerong Luo. "Joint Equalization and Raptor Decoding for Underwater Acoustic Communication." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 126–35. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69066-3_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Yu, Zibin, Hangfang Zhao, Wen Xu, and Xianyi Gong. "A Turbo Equalization Based on a Sparse Doubly Spread Acoustic Channels Estimation." In Underwater Acoustics and Ocean Dynamics, 57–61. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2422-1_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Li, Bo, Yu Zhao, Hongjuan Yang, Gongliang Liu, and Xiyuan Peng. "The Joint Channel Equalization and Estimation Algorithm for Underwater Acoustic Channel." In Lecture Notes in Electrical Engineering, 315–22. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6571-2_38.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Ning, Xiaoling, Zhong Liu, and Yasong Luo. "Research on Variable Step-Size Blind Equalization Algorithm Based on Normalized RBF Neural Network in Underwater Acoustic Communication." In Advances in Neural Networks – ISNN 2009, 1063–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01513-7_117.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Luo, Yasong, Zhong Liu, Pengfei Peng, and Xuezhi Fu. "Phase Self-amending Blind Equalization Algorithm Using Feedforward Neural Network for High-Order QAM Signals in Underwater Acoustic Channels." In Advances in Neural Networks – ISNN 2009, 538–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01513-7_59.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Zhao, Liang, and Jianhua Ge. "Iterative Equalization and Decoding Scheme for Underwater Acoustic Coherent Communications." In Underwater Acoustics. InTech, 2012. http://dx.doi.org/10.5772/28986.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Acoustic equalization"

1

Cannelli, Loris, Geert Leus, Henry Dol, and Paul van Walree. "Adaptive turbo equalization for underwater acoustic communication." In 2013 MTS/IEEE OCEANS. IEEE, 2013. http://dx.doi.org/10.1109/oceans-bergen.2013.6608150.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Pinho, Vinicius, Rafael Chaves, and Marcello Campos. "On Equalization Performance in Underwater Acoustic Communication." In XXXVI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais. Sociedade Brasileira de Telecomunicações, 2018. http://dx.doi.org/10.14209/sbrt.2018.207.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Youcef, Abdelhakim, Christophe Laot, and Karine Amis. "Adaptive frequency-domain equalization for underwater acoustic communications." In OCEANS 2011 - SPAIN. IEEE, 2011. http://dx.doi.org/10.1109/oceans-spain.2011.6003626.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Tao, Jun, Yanbo Wu, Qisong Wu, and Xiao Han. "Kalman Filter Based Equalization for Underwater Acoustic Communications." In OCEANS 2019 - Marseille. IEEE, 2019. http://dx.doi.org/10.1109/oceanse.2019.8866875.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Zhong, Liu, and Ning Xiao-ling. "Comparison of equalization algorithms for underwater acoustic channels." In 2012 2nd International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 2012. http://dx.doi.org/10.1109/iccsnt.2012.6526324.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Ling, Jun, Xing Tan, Jian Li, and Magnus Lundberg Nordenvaad. "Efficient channel equalization for MIMO underwater acoustic communications." In 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2010. http://dx.doi.org/10.1109/sam.2010.5606766.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Green, Dale, and M. Oussama Damen. "MMSE-Lattice Sequential Equalization of Underwater Acoustic Channels." In Oceans 2007. IEEE, 2007. http://dx.doi.org/10.1109/oceans.2007.4449138.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Rafati, Amirhossein, Huang Lou, Yahong Rosa Zheng, and Chengshan Xiao. "Soft feedback turbo equalization for underwater acoustic communications." In OCEANS 2011. IEEE, 2011. http://dx.doi.org/10.23919/oceans.2011.6107184.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Farcas, Calin A., Ervin Szopos, Ioana Saracut, Marius Neag, and Marina D. Topa. "Objective assessement of equalization methods using acoustic parameters." In 2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA). IEEE, 2019. http://dx.doi.org/10.23919/spa.2019.8936725.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Yang, Xiaoxia, Haibin Wang, and Jun Wang. "Multichannel decision feedback equalization in underwater acoustic communication." In ADVANCES IN OCEAN ACOUSTICS: Proceedings of the 3rd International Conference on Ocean Acoustics (OA2012). AIP, 2012. http://dx.doi.org/10.1063/1.4765941.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Acoustic equalization"

1

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.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

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.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Smith, David A., Alan Willner, and Kathryn Li. Optically-Amplified Scalable WDM Networks Using Acousto-Optic Filters for Amplification Gain Equalization and Signal Routing. Fort Belvoir, VA: Defense Technical Information Center, October 1997. http://dx.doi.org/10.21236/ada334120.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Acoustic equalization' for particular source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography