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Journal articles on the topic 'Adaptive Processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Brookner, E., and J. M. Howell. "Adaptive-adaptive array processing." Proceedings of the IEEE 74, no. 4 (1986): 602–4. http://dx.doi.org/10.1109/proc.1986.13507.

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2

Saxena, Ms Chhavi, Dr P. D. Murarka, and Dr Hemant Gupta. "ECG Signals Processing using Adaptive Linear Filters." International Journal of Trend in Scientific Research and Development Volume-1, Issue-5 (August 31, 2017): 496–502. http://dx.doi.org/10.31142/ijtsrd2342.

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3

Deshpande, Amol, Zachary Ives, and Vijayshankar Raman. "Adaptive Query Processing." Foundations and Trends® in Databases 1, no. 1 (2007): 1–140. http://dx.doi.org/10.1561/1900000001.

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4

Brewster, R. L. "Adaptive Signal Processing." Electronics and Power 32, no. 7 (1986): 545. http://dx.doi.org/10.1049/ep.1986.0314.

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5

Morgan, D. "Adaptive signal processing." IEEE Transactions on Acoustics, Speech, and Signal Processing 34, no. 4 (August 1986): 1017–18. http://dx.doi.org/10.1109/tassp.1986.1164869.

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6

Wright, J. Nelson. "Adaptive persistence processing." Journal of the Acoustical Society of America 102, no. 2 (August 1997): 688. http://dx.doi.org/10.1121/1.421034.

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7

Kabakchiev, Chr, B. Vassileva, and I. Miteva. "Adaptive Doppler processing technique." Mathematics and Computers in Simulation 43, no. 2 (February 1997): 203–8. http://dx.doi.org/10.1016/s0378-4754(96)00067-5.

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8

Sibul, Leon H., and Teresa L. Dixon. "Environmentallly adaptive signal processing." Journal of the Acoustical Society of America 101, no. 5 (May 1997): 3157. http://dx.doi.org/10.1121/1.419091.

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9

Siderius, Martin, Heechun Song, Peter Gerstoft, William S. Hodgkiss, Paul Hursky, and Chris Harrison. "Adaptive passive fathometer processing." Journal of the Acoustical Society of America 127, no. 4 (April 2010): 2193–200. http://dx.doi.org/10.1121/1.3303985.

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10

Gabriel, W. F. "Adaptive processing array systems." Proceedings of the IEEE 80, no. 1 (1992): 152–62. http://dx.doi.org/10.1109/5.119574.

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11

Cowan, C. F. N., R. F. Woods, J. P. Heron, P. Power, and F. J. Sweeney. "Advances in adaptive signal processing: totally adaptive systems." Annual Reviews in Control 25 (January 2001): 55–64. http://dx.doi.org/10.1016/s1367-5788(01)00006-2.

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12

Cowan, C. F. N., R. F. Woods, J. P. Heron, P. Power, and F. J. Sweeney. "Advances in Adaptive Signal Processing: Totally Adaptive Systems." IFAC Proceedings Volumes 31, no. 22 (August 1998): 185–94. http://dx.doi.org/10.1016/s1474-6670(17)35941-4.

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13

Musikhin, Vladislav I. "Polyspectral Processing in Adaptive Filtering." Ural Radio Engineering Journal 2, no. 3 (2018): 32–41. http://dx.doi.org/10.15826/urej.2018.2.3.003.

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14

Kaznacheeva, E. S., V. M. Kuz’kin, G. A. Lyakhov, S. A. Pereselkov, and S. A. Tkachenko. "Adaptive Algorithms for Interferometric Processing." Physics of Wave Phenomena 28, no. 3 (July 2020): 267–73. http://dx.doi.org/10.3103/s1541308x20030103.

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15

Baggeroer, Arthur B. "Partially adaptive matched‐field processing." Journal of the Acoustical Society of America 101, no. 5 (May 1997): 3046. http://dx.doi.org/10.1121/1.418681.

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16

Donald, J., and L. Akers. "An adaptive neural processing node." IEEE Transactions on Neural Networks 4, no. 3 (May 1993): 413–26. http://dx.doi.org/10.1109/72.217183.

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17

Resnikoff, Howard L. "Wavelets and adaptive signal processing." Optical Engineering 31, no. 6 (1992): 1229. http://dx.doi.org/10.1117/12.57515.

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18

Singh, Hema, and Rakesh Mohan Jha. "Trends in Adaptive Array Processing." International Journal of Antennas and Propagation 2012 (2012): 1–20. http://dx.doi.org/10.1155/2012/361768.

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Enormous progress has been made during the past five decades in the area of adaptive array processing. Increased computational power has resulted in many practical applications of optimum algorithms. The present paper deals with many facets of array signal processing and adaptive beam forming. It provides a comprehensive description of various beam-forming schemes, adaptive algorithms to adjust the required weighting on antenna elements, direction-of-arrival estimation methods, including their performance comparison. The effects of various types of errors on the performance of an array system are illustrated along with their remedial measures. Since array signal processing has widespread applications, the study is carried out across various disciplines.

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19

Haykin, Simon. "Guest Editorial: Adaptive Signal Processing." Optical Engineering 31, no. 6 (1992): 1143. http://dx.doi.org/10.1117/12.60706.

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20

Lindquist, C. "Book reviews - Adaptive signal processing." IEEE Control Systems Magazine 7, no. 4 (August 1987): 51. http://dx.doi.org/10.1109/mcs.1987.1105343.

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21

Harteneck, M., and R. W. Stewart. "Adaptive signal processing JAVA applet." IEEE Transactions on Education 44, no. 2 (May 2001): 6 pp. http://dx.doi.org/10.1109/13.925850.

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22

Wellstead, P. E. "Book Review: Adaptive Signal Processing." International Journal of Electrical Engineering & Education 23, no. 4 (October 1986): 375–76. http://dx.doi.org/10.1177/002072098602300429.

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23

Moses, R. L., and A. A. Beex. "Instrumental variable adaptive array processing." IEEE Transactions on Aerospace and Electronic Systems 24, no. 2 (March 1988): 192–202. http://dx.doi.org/10.1109/7.1053.

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24

Chakrabarti, N. B. "Transform Domain Adaptive Signal Processing." IETE Journal of Research 35, no. 2 (March 1989): 52–60. http://dx.doi.org/10.1080/03772063.1989.11436792.

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25

Aleksander, I., and M. J. Dobree Wilson. "Adaptive windows for image processing." IEE Proceedings E Computers and Digital Techniques 132, no. 5 (1985): 233. http://dx.doi.org/10.1049/ip-e.1985.0034.

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26

SAYED, A. H., and C. G. LOPES. "Adaptive Processing over Distributed Networks." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E90-A, no. 8 (August 1, 2007): 1504–10. http://dx.doi.org/10.1093/ietfec/e90-a.8.1504.

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27

Poulsen, Andrew J., Arthur B. Baggeroer, Jonathan Paul Kitchens, and Jennifer A. Watson. "Robust Adaptive Vector Sensor Processing." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 3438. http://dx.doi.org/10.1121/1.2934230.

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28

Debayle, Johan, and Jean-Charles Pinoli. "General Adaptive Neighborhood Image Processing:." Journal of Mathematical Imaging and Vision 25, no. 2 (August 14, 2006): 245–66. http://dx.doi.org/10.1007/s10851-006-7451-8.

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29

Debayle, Johan, and Jean-Charles Pinoli. "General Adaptive Neighborhood Image Processing." Journal of Mathematical Imaging and Vision 25, no. 2 (August 14, 2006): 267–84. http://dx.doi.org/10.1007/s10851-006-7452-7.

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30

Chen, Walter Y., and Richard A. Haddad. "Dual mode adaptive signal processing." Computers & Electrical Engineering 18, no. 3-4 (May 1992): 261–75. http://dx.doi.org/10.1016/0045-7906(92)90019-a.

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31

Wang, Hongli, Bin Guo, Jiaqi Liu, Sicong Liu, Yungang Wu, and Zhiwen Yu. "Context-aware Adaptive Surgery." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 3 (September 9, 2021): 1–22. http://dx.doi.org/10.1145/3478073.

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Abstract:

Deep Neural Networks (DNNs) have made massive progress in many fields and deploying DNNs on end devices has become an emerging trend to make intelligence closer to users. However, it is challenging to deploy large-scale and computation-intensive DNNs on resource-constrained end devices due to their small size and lightweight. To this end, model partition, which aims to partition DNNs into multiple parts to realize the collaborative computing of multiple devices, has received extensive research attention. To find the optimal partition, most existing approaches need to run from scratch under given resource constraints. However, they ignore that resources of devices (e.g., storage, battery power), and performance requirements (e.g., inference latency), are often continuously changing, making the optimal partition solution change constantly during processing. Therefore, it is very important to reduce the tuning latency of model partition to realize the real-time adaption under the changing processing context. To address these problems, we propose the Context-aware Adaptive Surgery (CAS) framework to actively perceive the changing processing context, and adaptively find the appropriate partition solution in real-time. Specifically, we construct the partition state graph to comprehensively model different partition solutions of DNNs by import context resources. Then "the neighbor effect" is proposed, which provides the heuristic rule for the search process. When the processing context changes, CAS adopts the runtime search algorithm, Graph-based Adaptive DNN Surgery (GADS), to quickly find the appropriate partition that satisfies resource constraints under the guidance of the neighbor effect. The experimental results show that CAS realizes adaptively rapid tuning of the model partition solutions in 10ms scale even for large DNNs (2.25x to 221.7x search time improvement than the state-of-the-art researches), and the total inference latency still keeps the same level with baselines.

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32

Tran, Tri Minh, and Byung Suk Lee. "Distributed Adaptive Windowed Stream Join Processing." International Journal of Distributed Systems and Technologies 2, no. 2 (April 2011): 59–81. http://dx.doi.org/10.4018/jdst.2011040104.

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This paper presents an adaptive framework for processing a window-based multi-way join query over distributed data streams. The framework integrates distributed plan modification and distributed plan migration within the same scope by using a building block called the node operator set (NOS). An NOS is housed in each node that participates in the join execution, and specifies the set of atomic operations to be performed locally at the host node to execute its share of the global execution plan. The plan modification and migration techniques presented are for the case of updating the NOSs centralized at a single node and the case of updating them distributed at each node. The plan modification is triggered by the change of stream statistics and adjusts the join execution order and placement greedily to satisfy a cost invariant. The plan migration uses the distributed track strategy to accelerate the migration of window extents to new nodes. The migration of all window extents is synchronized. Experiments confirm the effectiveness of the developed adaptive framework on reducing the join execution cost and indicate a small additional adaptation-overhead for distributing the NOS update.

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33

Murano, K. "Adaptive Signal Processing Applied in Telecommunications." IFAC Proceedings Volumes 25, no. 14 (July 1992): 431–41. http://dx.doi.org/10.1016/s1474-6670(17)50772-7.

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34

Pfaffmann, Jeffrey O., and Michael Conrad. "Adaptive information processing in microtubule networks." Biosystems 55, no. 1-3 (February 2000): 47–57. http://dx.doi.org/10.1016/s0303-2647(99)00082-9.

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35

Combaud, M. "Adaptive processing at the subarray level." Aerospace Science and Technology 3, no. 2 (February 1999): 93–105. http://dx.doi.org/10.1016/s1270-9638(99)80033-9.

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36

Nairne, James S., and Josefa N. S. Pandeirada. "Adaptive memory: Is survival processing special?" Journal of Memory and Language 59, no. 3 (October 2008): 377–85. http://dx.doi.org/10.1016/j.jml.2008.06.001.

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37

Sztipanovits, Janos, Gabor Karsai, and Ted Bapty. "Self-adaptive software for signal processing." Communications of the ACM 41, no. 5 (May 1998): 66–73. http://dx.doi.org/10.1145/274946.274958.

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38

Stewart, R. W., M. Harteneck, and S. Weiss. "Interactive teaching of adaptive signal processing." Engineering Science & Education Journal 9, no. 4 (August 1, 2000): 161–68. http://dx.doi.org/10.1049/esej:20000404.

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39

Wagstaff, Ronald A., and Jackson A. Mobbs. "Environmentally sensitive adaptive fluctuation‐based processing." Journal of the Acoustical Society of America 101, no. 5 (May 1997): 3027–28. http://dx.doi.org/10.1121/1.418569.

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40

Nejevenko, E. S., and A. A. Sotnikov. "Adaptive modeling for hydroacoustic signal processing." Pattern Recognition and Image Analysis 16, no. 1 (January 2006): 5–8. http://dx.doi.org/10.1134/s1054661806010020.

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41

Karpathiotakis, Manos, Miguel Branco, Ioannis Alagiannis, and Anastasia Ailamaki. "Adaptive query processing on RAW data." Proceedings of the VLDB Endowment 7, no. 12 (August 2014): 1119–30. http://dx.doi.org/10.14778/2732977.2732986.

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42

Teuner, A., and B. J. Hosticka. "Adaptive Gabor transformation for image processing." IEEE Transactions on Image Processing 2, no. 1 (1993): 112–17. http://dx.doi.org/10.1109/83.210872.

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43

Tracey, Brian, Srinivas Turaga, and Nigel Lee. "Reduced beamset adaptive matched field processing." Journal of the Acoustical Society of America 113, no. 4 (April 2003): 2263. http://dx.doi.org/10.1121/1.4780490.

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44

Hernández, Adrián, and José M. Amigó. "Multilayer adaptive networks in neuronal processing." European Physical Journal Special Topics 227, no. 10-11 (November 2018): 1039–49. http://dx.doi.org/10.1140/epjst/e2018-800037-y.

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45

McLean, G. F., and M. E. Jernigan. "Indicator functions for adaptive image processing." Journal of the Optical Society of America A 8, no. 1 (January 1, 1991): 141. http://dx.doi.org/10.1364/josaa.8.000141.

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46

Nairne, James S., Sarah R. Thompson, and Josefa N. S. Pandeirada. "Adaptive memory: Survival processing enhances retention." Journal of Experimental Psychology: Learning, Memory, and Cognition 33, no. 2 (2007): 263–73. http://dx.doi.org/10.1037/0278-7393.33.2.263.

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47

Zhenyu Zhu and H. R. Sadjadpour. "An adaptive per-survivor processing algorithm." IEEE Transactions on Communications 50, no. 11 (November 2002): 1716–18. http://dx.doi.org/10.1109/tcomm.2002.805272.

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48

Popov, D. I. "ADAPTIVE INTERPERIOD PROCESSING OF MULTIFREQUENCY SIGNALS." Vestnik of Ryazan State Radio Engineering University 64 (2018): 17–22. http://dx.doi.org/10.21667/1995-4565-2018-64-2-17-22.

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49

Cioffi, J. "The block-processing FTF adaptive algorithm." IEEE Transactions on Acoustics, Speech, and Signal Processing 34, no. 1 (February 1986): 77–90. http://dx.doi.org/10.1109/tassp.1986.1164799.

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50

Richter, G. M., P. Böhm, H. Lorenz, A. Priebe, and M. Capaccioli. "Adaptive filtering in astronomical image processing." Astronomische Nachrichten: A Journal on all Fields of Astronomy 312, no. 6 (1991): 345–49. http://dx.doi.org/10.1002/asna.2113120602.

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