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Relevant bibliographies by topics / Adaptive Processing

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Academic literature on the topic 'Adaptive Processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Adaptive Processing"

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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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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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Adaptive Processing"

1

Yang, Ho. "Partially adaptive space-time processing." Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/13028.

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Seliktar, Yaron. "Space-time adaptive monopulse processing." Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/13075.

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Jahanchahi, Cyrus. "Quaternion valued adaptive signal processing." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/24165.

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Recent developments in sensor technology, human centered computing and robotics have brought to light new classes of multidimensional data which are naturally represented as three- or four-dimensional vector-valued processes. Such signals are readily modeled as real vectors in R3 and R4, however, it has become apparent that there are advantages in processing such data in division algebras - the quaternion domain. The progress in the statistics of quaternion variable, particularly augmented statistics and widely linear modeling, has opened up a new front of research in vector sensor modeling, however, there are several key problems that need to be addressed in order to exploit the full power of quaternions in statistical signal processing. The principal problem lies in the lack of a mathematical framework, such as the CR-calculus in the complex domain, for the differentiation of non-holomorphic functions. Since most functions (including typical cost functions) in the quaternion domain are non-holomorphic, as defined by the Cauchy-Riemann-Fueter (CRF) condition, this presents a severe obstacle to solving optimisation problems and developing adaptive filtering algorithms in the quaternion domain. To this end, we develop the HR-calculus, an extension of the CR-calculus, allowing the differentiation of non-holomorphic functions. This is followed by the introduction of the I-gradient, enabling for generic extensions of complex valued algorithms to be derived. Using this unified framework we introduce the quaternion least mean square (QLMS), quaternion recursive least squares (QRLS), quaternion affine projection algorithm (QAPA) and quaternion Kalman filter. These estimators are made optimal for the processing of noncircular data, by proposing widely linear extensions of their standard versions. Convergence and steady state properties of these adaptive estimators are analysed and validated experimentally via simulations on both synthetic and real world signals.

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Beck, Rainer Johannes. "Adaptive optics for laser processing." Thesis, Heriot-Watt University, 2011. http://hdl.handle.net/10399/2462.

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The overall aim of the work presented in this thesis is to develop an adaptive optics (AO) technique for application to laser-based manufacturing processes. The Gaussian beam shape typically coming from a laser is not always ideal for laser machining. Wavefront modulators, such as deformable mirrors (DM) and liquid crystal spatial light modulators (SLM), enable the generation of a variety of beam shapes and furthermore offer the ability to alter the beam shape during the actual process. The benefits of modifying the Gaussian beam shape by means of a deformable mirror towards a square flat top profile for nanosecond laser marking and towards a ring shape intensity distribution for millisecond laser drilling are presented. Limitations of the beam shaping capabilities of DM are discussed. The application of a spatial light modulator to nanosecond laser micromachining is demonstrated for the first time. Heat sinking is introduced to increase the power handling capabilities. Controllable complex beam shapes can be generated with sufficient intensity for direct laser marking. Conventional SLM devices suffer from flickering and hence a process synchronisation is introduced to compensate for its impact on the laser machining result. For alternative SLM devices this novel technique can be beneficial when fast changes of the beam shape during the laser machining are required. The dynamic nature of SLMs is utilised to improve the marking quality by reducing the inherent speckle distribution of the generated beam shape. In addition, adaptive feedback on the intensity distribution can further improve the quality of the laser machining. In general, beam shaping by means of AO devices enables an increased flexibility and an improved process control, and thus has a significant potential to be used in laser materials processing.

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Testoni, Nicola <1980&gt. "Adaptive multiscale biological signal processing." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/1122/.

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Biological processes are very complex mechanisms, most of them being accompanied by or manifested as signals that reflect their essential characteristics and qualities. The development of diagnostic techniques based on signal and image acquisition from the human body is commonly retained as one of the propelling factors in the advancements in medicine and biosciences recorded in the recent past. It is a fact that the instruments used for biological signal and image recording, like any other acquisition system, are affected by non-idealities which, by different degrees, negatively impact on the accuracy of the recording. This work discusses how it is possible to attenuate, and ideally to remove, these effects, with a particular attention toward ultrasound imaging and extracellular recordings. Original algorithms developed during the Ph.D. research activity will be examined and compared to ones in literature tackling the same problems; results will be drawn on the base of comparative tests on both synthetic and in-vivo acquisitions, evaluating standard metrics in the respective field of application. All the developed algorithms share an adaptive approach to signal analysis, meaning that their behavior is not dependent only on designer choices, but driven by input signal characteristics too. Performance comparisons following the state of the art concerning image quality assessment, contrast gain estimation and resolution gain quantification as well as visual inspection highlighted very good results featured by the proposed ultrasound image deconvolution and restoring algorithms: axial resolution up to 5 times better than algorithms in literature are possible. Concerning extracellular recordings, the results of the proposed denoising technique compared to other signal processing algorithms pointed out an improvement of the state of the art of almost 4 dB.

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Shah, Ijteba-ul-Hasnain. "Constrained adaptive natural gradient algorithms for adaptive array processing." Thesis, University of Strathclyde, 2011. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=15646.

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eurviriyanukul, kwanchai. "adaptive query processing in pipelined plans." Thesis, University of Manchester, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492914.

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This thesis presents an approach to enable changes to partially evaluated pipelined Query-Execution Plans (QEPs) at run-time to recover from optimisation mistakes in cardinality estimation according to the absences of accurate statistics. These mistakes may influence an optimiser to select in-efficient QEPs.

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Lopes, Cassio Guimaraes. "Distributed cooperative strategies for adaptive processing." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1581123071&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Stoian, Razvan. "Adaptive techniques for ultrafast laser material processing." Habilitation à diriger des recherches, Université Jean Monnet - Saint-Etienne, 2008. http://tel.archives-ouvertes.fr/tel-00352662.

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Le besoin d'une très grande précision lors du traitement des matériaux par laser a fortement encouragé le développement des études de l'effet des impulsions ultra brèves pour la structuration des matériaux à une échelle micro et nano métrique. Une diffusion d'énergie minimale et une forte non linéarité de l'interaction permet un important confinement énergétique à des échelles les plus petites possibles. La possibilité d'introduire des changements de phases rapides et même de créer de nouveaux états de matière ayant des propriétés optimisées et des fonctions améliorées donne aux impulsions ultra brèves de sérieux arguments pour être utilisées dans des dispositifs très précis de transformation et de structuration des matériaux. L'étude de ces mécanismes de structuration et, en particulier, de leurs caractéristiques dynamiques, est une clé pour l'optimisation de l'interaction laser-matière suivant de nombreux critères utiles pour les procédés laser : efficacité, précision, qualité. Ce mémoire synthétise les travaux de l'auteur sur l'étude statique et dynamique du dépôt d'énergie ultra rapide, avec application aux procédés laser. La connaissance de la réponse dynamique des matériaux après irradiation laser ultra brève montre que les temps de relaxation pilotent l'interaction lumière-matière. Il est alors possible d'adapter l'énergie déposée à la réponse du matériau en utilisant les toutes récentes techniques de mise en forme spatio temporelle de faisceaux. Un couplage optimal de l'énergie donne la possibilité d'orienter la réponse du matériau vers un résultat recherché, offrant une grande flexibilité de contrôle des procédés et, sans doute, la première étape du développement de procédés « intelligents ».

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Östlund, Nils. "Adaptive signal processing of surface electromyogram signals." Doctoral thesis, Umeå universitet, Strålningsvetenskaper, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-743.

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Electromyography is the study of muscle function through the electrical signals from the muscles. In surface electromyography the electrical signal is detected on the skin. The signal arises from ion exchanges across the muscle fibres’ membranes. The ion exchange in a motor unit, which is the smallest unit of excitation, produces a waveform that is called an action potential (AP). When a sustained contraction is performed the motor units involved in the contraction will repeatedly produce APs, which result in AP trains. A surface electromyogram (EMG) signal consists of the superposition of many AP trains generated by a large number of active motor units. The aim of this dissertation was to introduce and evaluate new methods for analysis of surface EMG signals. An important aspect is to consider where to place the electrodes during the recording so that the electrodes are not located over the zone where the neuromuscular junctions are located. A method that could estimate the location of this zone was presented in one study. The mean frequency of the EMG signal is often used to estimate muscle fatigue. For signals with low signal-to-noise ratio it is important to limit the integration intervals in the mean frequency calculations. Therefore, a method that improved the maximum frequency estimation was introduced and evaluated in comparison with existing methods. The main methodological work in this dissertation was concentrated on finding single motor unit AP trains from EMG signals recorded with several channels. In two studies single motor unit AP trains were enhanced by using filters that maximised the kurtosis of the output. The first of these studies used a spatial filter, and in the second study the technique was expanded to include filtration in time. The introduction of time filtration resulted in improved performance, and when the method was evaluated in comparison with other methods that use spatial and/or temporal filtration, it gave the best performance among them. In the last study of this dissertation this technique was used to compare AP firing rates and conduction velocities in fibromyalgia patients as compared with a control group of healthy subjects. In conclusion, this dissertation has resulted in new methods that improve the analysis of EMG signals, and as a consequence the methods can simplify physiological research projects.

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Books on the topic "Adaptive Processing"

1

D, Stearns Samuel, ed. Adaptive signal processing. Englewood Cliffs, N.J: Prentice-Hall, 1985.

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2

Davisson, L. D., and G. Longo, eds. Adaptive Signal Processing. Vienna: Springer Vienna, 1991. http://dx.doi.org/10.1007/978-3-7091-2840-4.

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Alexander, S. Thomas. Adaptive Signal Processing. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4612-4978-8.

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Adali, Tülay, and Simon Haykin, eds. Adaptive Signal Processing. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470575758.

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Benesty, Jacob, and Yiteng Huang, eds. Adaptive Signal Processing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-11028-7.

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Deshpande, Amol. Adaptive query processing. Boston: Now, 2007.

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Widrow, Bernard. Adaptive signal processing and adaptive neural networks. Piscataway, NJ: The Institute of Electrical and Electronics Engineers, 1992.

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Haykin, Simon, ed. Adaptive Radar Signal Processing. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0470069120.

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9

Clarkson, Peter M. Optimal and adaptive signal processing. Boca Raton: CRC Press, 1993.

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Nitzberg, Ramon. Adaptive signal processing for radar. Boston: Artech House, 1991.

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Book chapters on the topic "Adaptive Processing"

1

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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Ives, Zachary. "Adaptive Stream Processing." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_11-2.

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Casey, Stephen D. "Adaptive Signal Processing." In Excursions in Harmonic Analysis, Volume 4, 261–90. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20188-7_11.

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Pitoura, Evaggelia. "Adaptive Query Processing." In Encyclopedia of Database Systems, 61–63. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_865.

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Ives, Zachary G. "Adaptive Stream Processing." In Encyclopedia of Database Systems, 63–68. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_11.

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Pitoura, Evaggelia. "Adaptive Query Processing." In Encyclopedia of Database Systems, 50–52. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_865.

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Ives, Zachary. "Adaptive Stream Processing." In Encyclopedia of Database Systems, 52–56. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_11.

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Pitoura, Evaggelia. "Adaptive Query Processing." In Encyclopedia of Database Systems, 1–2. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_865-2.

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Mulgrew, Bernard. "Adaptive filters." In Digital Signal Processing, 213–45. London: Macmillan Education UK, 2003. http://dx.doi.org/10.1057/978-1-137-44655-8_8.

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Chonavel, Thierry. "Adaptive Estimation." In Statistical Signal Processing, 231–48. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0139-0_16.

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Conference papers on the topic "Adaptive Processing"

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Deshpande, A., J. M. Hellerstein, and V. Raman. "Adaptive query processing." In the 2006 ACM SIGMOD international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1142473.1142603.

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Gu, Huaijin. "Angle-Tracking Adaptive Array -- Adaptive-Adaptive Array Processing." In 2007 IEEE Radar Conference. IEEE, 2007. http://dx.doi.org/10.1109/radar.2007.374313.

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Thiébaut, Éric M., Michel Tallon, Maud Langlois, Clémentine Béchet, Gil Moretto, Bernard F. Gelly, and Loïc Denis. "Innovative real-time processing for solar adaptive optics." In Adaptive Optics Systems VI, edited by Dirk Schmidt, Laura Schreiber, and Laird M. Close. SPIE, 2018. http://dx.doi.org/10.1117/12.2313776.

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Shen, Bob, Mike Tracy, Youn-Seo Roh, and Fu-Kuo Chang. "Built-in piezoelectrics for processing and health monitoring of composite structures." In Adaptive Structures Forum. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1996. http://dx.doi.org/10.2514/6.1996-1310.

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Parker, Michael. "Adaptive Array Processing Architecture." In NAECON 2019 - IEEE National Aerospace and Electronics Conference. IEEE, 2019. http://dx.doi.org/10.1109/naecon46414.2019.9058177.

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"Adaptive antennas, signal processing." In 2005 5th International Conference on Antenna Theory and Techniques. IEEE, 2005. http://dx.doi.org/10.1109/icatt.2005.1496940.

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Xu, Zhengdao, and Arno Jacobsen. "Adaptive location constraint processing." In the 2007 ACM SIGMOD international conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1247480.1247545.

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"7 - Adaptive Array Processing." In 2005 Microwave Electronics: Measurements, Identification, Applications. IEEE, 2005. http://dx.doi.org/10.1109/ssp.2005.1628602.

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Paranjape, Raman B., Rangaraj M. Rangayyan, William M. Morrow, and H. N. Nguyen. "Adaptive-neighborhood image processing." In Applications in Optical Science and Engineering, edited by Petros Maragos. SPIE, 1992. http://dx.doi.org/10.1117/12.131438.

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Weischedel, Ralph. "Adaptive natural language processing." In the workshop. Morristown, NJ, USA: Association for Computational Linguistics, 1991. http://dx.doi.org/10.3115/112405.1138642.

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Reports on the topic "Adaptive Processing"

1

Vanderlugt, A., and Reeder N. Ward. Adaptive Presort Processing. Fort Belvoir, VA: Defense Technical Information Center, October 1991. http://dx.doi.org/10.21236/ada243286.

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Himed, Braham. Conformal Array Adaptive Processing. Fort Belvoir, VA: Defense Technical Information Center, March 2006. http://dx.doi.org/10.21236/ada446076.

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MITRE CORP BEDFORD MA. MITRE Adaptive Processing Capability. Fort Belvoir, VA: Defense Technical Information Center, June 1994. http://dx.doi.org/10.21236/ada281078.

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Albert, T. R. Adaptive Signal Processing at NOSC. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada250245.

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Goldstein, J. S., and Irving S. Reed. Adaptive CFAR Detection and Reduced-Rank Space-Time Adaptive Processing. Fort Belvoir, VA: Defense Technical Information Center, March 1997. http://dx.doi.org/10.21236/ada323841.

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Tufts, Donald W. Adaptive, Robust, High-Resolution Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, March 1990. http://dx.doi.org/10.21236/ada223728.

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Brady, David J., Mark A. Neifeld, and Travis Blalock. Adaptive Multiplexed Wavelength and Spatial Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada449523.

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Oppenehim, Alan, and Arthur Baggeroer. Adaptive Array Processing in Uncertain Inhomogeneous Media. Fort Belvoir, VA: Defense Technical Information Center, August 1992. http://dx.doi.org/10.21236/ada254418.

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Wagner, Kelvin, Shawn Kraut, and Lloyd Griffiths. Efficient Adaptive Optical Processing for Sonar Arrays. Fort Belvoir, VA: Defense Technical Information Center, April 1999. http://dx.doi.org/10.21236/ada362538.

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Janni, Joseph, and Stuart Jefferies. Consortium for Adaptive Optics and Image Post-Processing. Fort Belvoir, VA: Defense Technical Information Center, June 2008. http://dx.doi.org/10.21236/ada483613.

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