Relevant bibliographies by topics / Signal complexity

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Signal complexity'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Signal complexity"

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Iqbal, Jameel, Li Sun, and Mone Zaidi. "Complexity in signal transduction." Annals of the New York Academy of Sciences 1192, no. 1 (2010): 238–44. http://dx.doi.org/10.1111/j.1749-6632.2010.05388.x.

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Warr, Paul A., and Alan M. Potter. "A Reduced-Complexity Mixer Linearization Scheme." Research Letters in Communications 2009 (2009): 1–4. http://dx.doi.org/10.1155/2009/541084.

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Measurement results of the signals emanating from both IF and LO ports of a double balanced mixer are presented, and, thus, it is shown that the linearization of the output in a down-converting mixer by the summation of the IF signal and the signal emanating from the LO or RF port is feasible. Feedforward-based architectures for the linearization of down-conversion mixers are introduced that exploit this phenomenon, and linearity performance results of the frequency translation of both two-tone and TETRA-modulated signals are presented. This technique employs only a single mixer and hence over
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RAGHAVENDRA, B. S., and D. NARAYANA DUTT. "SIGNAL CHARACTERIZATION USING FRACTAL DIMENSION." Fractals 18, no. 03 (2010): 287–92. http://dx.doi.org/10.1142/s0218348x10004968.

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Fractal Dimensions (FD) are one of the popular measures used for characterizing signals. They have been used as complexity measures of signals in various fields including speech and biomedical applications. However, proper interpretation of such analyses has not been thoroughly addressed. In this paper, we study the effect of various signal properties on FD and interpret results in terms of classical signal processing concepts such as amplitude, frequency, number of harmonics, noise power and signal bandwidth. We have used Higuchi's method for estimating FDs. This study may help in gaining a b
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Bruni, Vittoria, Michela Tartaglione, and Domenico Vitulano. "A Signal Complexity-Based Approach for AM–FM Signal Modes Counting." Mathematics 8, no. 12 (2020): 2170. http://dx.doi.org/10.3390/math8122170.

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Frequency modulated signals appear in many applied disciplines, including geology, communication, biology and acoustics. They are naturally multicomponent, i.e., they consist of multiple waveforms, with specific time-dependent frequency (instantaneous frequency). In most practical applications, the number of modes—which is unknown—is needed for correctly analyzing a signal; for instance for separating each individual component and for estimating its instantaneous frequency. Detecting the number of components is a challenging problem, especially in the case of interfering modes. The Rényi Entro
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Klonowski, Włodzimierz, Pawel Stepien, and Robert Stepien. "Complexity Measures of Brain Electrophysiological Activity." Journal of Psychophysiology 24, no. 2 (2010): 131–35. http://dx.doi.org/10.1027/0269-8803/a000024.

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Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may
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Liu, Jizhen, Chao Cui, Qingwei Meng, Yali Shen, and Fang Fang. "IAE performance based signal complexity measure." Measurement 75 (November 2015): 255–62. http://dx.doi.org/10.1016/j.measurement.2015.07.038.

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Hegde, Ramanujan S., and Harris D. Bernstein. "The surprising complexity of signal sequences." Trends in Biochemical Sciences 31, no. 10 (2006): 563–71. http://dx.doi.org/10.1016/j.tibs.2006.08.004.

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Cho, Young-Hee, and Sang-Dong Yoo. "Emerging Complexity of Ethylene Signal Transduction." Journal of Plant Biology 52, no. 4 (2009): 283–88. http://dx.doi.org/10.1007/s12374-009-9038-6.

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Ay, Nihat, Jessica Flack, and David C. Krakauer. "Robustness and complexity co-constructed in multimodal signalling networks." Philosophical Transactions of the Royal Society B: Biological Sciences 362, no. 1479 (2007): 441–47. http://dx.doi.org/10.1098/rstb.2006.1971.

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In animal communication, signals are frequently emitted using different channels (e.g. frequencies in a vocalization) and different modalities (e.g. gestures can accompany vocalizations). We explore two explanations that have been provided for multimodality: (i) selection for high information transfer through dedicated channels and (ii) increasing fault tolerance or robustness through multichannel signals. Robustness relates to an accurate decoding of a signal when parts of a signal are occluded. We show analytically in simple feed-forward neural networks that while a multichannel signal can s
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Bhattacharya, Joydeep, and Eun-Jeong Lee. "Modulation of EEG Theta Band Signal Complexity by Music Therapy." International Journal of Bifurcation and Chaos 26, no. 01 (2016): 1650001. http://dx.doi.org/10.1142/s0218127416500012.

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The primary goal of this study was to investigate the impact of monochord (MC) sounds, a type of archaic sounds used in music therapy, on the neural complexity of EEG signals obtained from patients undergoing chemotherapy. The secondary goal was to compare the EEG signal complexity values for monochords with those for progressive muscle relaxation (PMR), an alternative therapy for relaxation. Forty cancer patients were randomly allocated to one of the two relaxation groups, MC and PMR, over a period of six months; continuous EEG signals were recorded during the first and last sessions. EEG sig
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Dissertations / Theses on the topic "Signal complexity"

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Bull, David R. "Signal processing techniques with reduced computational complexity." Thesis, Cardiff University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388006.

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Lallo, Madeline M. "Good Vibrations: Signal Complexity in Schizocosa Ethospecies." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1554215678769319.

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Shah, Kushal Yogeshkumar. "Computational Complexity of Signal Processing Functions in Software Radio." Cleveland State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=csu1292854939.

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Wang, Tong. "Low-complexity signal processing algorithms for wireless sensor networks." Thesis, University of York, 2012. http://etheses.whiterose.ac.uk/2844/.

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Recently, wireless sensor networks (WSNs) have attracted a great deal of research interest because of their unique features that allow a wide range of applications in the areas of military, environment, health and home. One of the most important constraints on WSNs is the low power consumption requirement as sensor nodes carry limited, generally irreplaceable, power sources. Therefore, low complexity and high energy efficiency are the most important design characteristics for WSNs. In this thesis, we focus on the development of low complexity signal processing algorithms for the physical layer
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Paraskevas, Alexandros. "Organisational crisis signal detection from a complexity thinking perspective." Thesis, Oxford Brookes University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.515276.

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Perry, Russell. "Low complexity adaptive equalisation for wireless applications." Thesis, University of Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389138.

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Ma, Hannan. "Iterative row-column algorithms for two-dimensional intersymbol interference channel equalization complexity reduction and performance enhancement /." Pullman, Wash. : Washington State University, 2010. http://www.dissertations.wsu.edu/Thesis/Summer2010/h_ma_062110.pdf.

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Thesis (M.S. in electrical engineering)--Washington State University, August 2010.<br>Title from PDF title page (viewed on July 28, 2010). "School of Electrical Engineering and Computer Science." Includes bibliographical references (p. 51).
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Kale, Kaustubh R. "Low complexity, narrow baseline beamformer for hand-held devices." [Gainesville, Fla.] : University of Florida, 2003. http://purl.fcla.edu/fcla/etd/UFE0001223.

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Sepehr, H. "Advanced adaptive signal processing techniques for low complexity speech enhancement applications." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1306808/.

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This thesis research is focused on using subband and multi rate adaptive signal processing techniques in order to develop practical speech enhancement algorithms. This thesis comprises of research on three different speech enhancement applications. Firstly, design of a novel method for attenuation of a siren signal in an emergency telephony system (by use of single source siren noise reduction algorithms) is investigated. The proposed method is based on wavelet filter banks and series of adaptive notch filters in order to detect and attenuate the siren noise signal with minimal effect on quali
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Page, Kevin J. "Reduced complexity interconnection and computation for digital signal processing in communications /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1997. http://wwwlib.umi.com/cr/ucsd/fullcit?p9804035.

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Books on the topic "Signal complexity"

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Sabadini, Irene, Daniele C. Struppa, and David F. Walnut, eds. Harmonic Analysis, Signal Processing, and Complexity. Birkhäuser Boston, 2005. http://dx.doi.org/10.1007/0-8176-4416-4.

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Bai, Lin. Low Complexity MIMO Detection. Springer US, 2012.

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Achilleas, Anastasopoulos, and Chen Xiaopeng, eds. Iterative detection: Adaptivity, complexity reduction, and applications. Kluwer Academic Publishers, 2001.

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Chugg, Keith M. Iterative detection: Adaptivity, complexity reduction, and applications. Kluwer Academic Publishers, 2001.

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Yarlagadda, R. K. Rao. Hadamard Matrix Analysis and Synthesis: With Applications to Communications and Signal/Image Processing. Springer US, 1997.

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Mitkowski, Wojciech. Advances in the Theory and Applications of Non-integer Order Systems: 5th Conference on Non-integer Order Calculus and Its Applications, Cracow, Poland. Springer International Publishing, 2013.

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Robert A. Welch Foundation Conference on Chemical Research (50th 2005 Houston, Tex.). Exploring the complexity of signaling pathways: The Robert A. Welch Foundation 50th Conference on Chemical Research : October 23-24, 2006, the Wyndam Greenspoint Hotel, Houston, Texas. Robert A. Welch Foundation, 2006.

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Houghton, A. Error Coding for Engineers. Springer US, 2001.

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Andrzej, Cichocki, Yeredor Arie, Zibulevsky Michael, and SpringerLink (Online service), eds. Latent Variable Analysis and Signal Separation: 10th International Conference, LVA/ICA 2012, Tel Aviv, Israel, March 12-15, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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Salazar, Addisson. On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling. Springer Berlin Heidelberg, 2013.

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Book chapters on the topic "Signal complexity"

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Losada, Ricardo A., and Richard G. Lyons. "Reducing CIC Filter Complexity." In Streamlining Digital Signal Processing. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118316948.ch6.

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Caulfield, H. J. "Space Time Complexity in Optical Computing." In Optical Signal Processing. Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-4006-9_4.

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Monteil, Thierry. "A Universal Oracle for Signal Machines." In Unveiling Dynamics and Complexity. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58741-7_30.

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Bai, Lin, Jinho Choi, and Quan Yu. "Signal Processing at Receivers: Detection Theory." In Low Complexity MIMO Receivers. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04984-7_2.

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Bai, Lin, Jinho Choi, and Quan Yu. "MIMO Detection: Vector Space Signal Detection." In Low Complexity MIMO Receivers. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04984-7_3.

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Brandejsky, Tomas. "Evolutionary Systems in Complex Signal Analysis." In Emergence, Complexity and Computation. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45438-7_10.

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Paradisi, Paolo, and Paolo Allegrini. "Intermittency-Driven Complexity in Signal Processing." In Complexity and Nonlinearity in Cardiovascular Signals. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58709-7_6.

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Gorin, A. L., D. B. Roe, and A. G. Greenberg. "On the Complexity of Pattern Recognition Algorithms on a Tree-Structured Parallel Computer." In Signal Processing. Springer US, 1990. http://dx.doi.org/10.1007/978-1-4684-6393-4_8.

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Azzini, Antonia, Mauro Dragoni, and Andrea G. B. Tettamanzi. "A Neuro-Evolutionary Approach to Electrocardiographic Signal Classification." In Evolution, Complexity and Artificial Life. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-37577-4_13.

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Zhang, Meng, Hao Wu, Jinwei Cai, and Wenshi Li. "Signal Complexity Measures Based on Ising Model." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5887-0_39.

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Conference papers on the topic "Signal complexity"

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Roztocki, Piotr, Michael Kues, Christian Reimer, et al. "Quantum photonic circuits for optical signal processing." In 2015 Spatiotemporal Complexity in Nonlinear Optics (SCNO). IEEE, 2015. http://dx.doi.org/10.1109/scno.2015.7324001.

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Li, Ling, and Ruiping Wang. "Complexity Analysis of Sleep EEG Signal." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5515699.

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Tsumura, K. "Signal complexity in cyclic consensus systems." In 2010 American Control Conference (ACC 2010). IEEE, 2010. http://dx.doi.org/10.1109/acc.2010.5530987.

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Kurths, J., U. Schwarz, A. Witt, R. Th Krampe, and M. Abel. "Measures of complexity in signal analysis." In Chaotic, fractal, and nonlinear signal processing. AIP, 1996. http://dx.doi.org/10.1063/1.51037.

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Schmieder, L., D. Mellon, and M. Saquib. "Signal direction finding for low complexity radar." In 2009 International Waveform Diversity and Design Conference. IEEE, 2009. http://dx.doi.org/10.1109/wddc.2009.4800304.

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Picone, J. "Managing software complexity in signal processing research." In Proceedings of ICASSP '93. IEEE, 1993. http://dx.doi.org/10.1109/icassp.1993.319430.

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Shafivulla, Sayyed, Aaqib Patel, and Mohammed Zafar Ali Khan. "Low Complexity Signal Detection in MIMO Systems." In 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall). IEEE, 2018. http://dx.doi.org/10.1109/vtcfall.2018.8690912.

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Dumenil, Arnaud, Elie Awwad, and Cyril Méasson. "Low-Complexity PDL-Resilient Signaling Design." In Signal Processing in Photonic Communications. OSA, 2019. http://dx.doi.org/10.1364/sppcom.2019.spth2e.3.

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Savory, Seb J., Md Saifuddin Faruk, and Xiang Li. "Low Complexity Coherent for Access Networks." In Signal Processing in Photonic Communications. OSA, 2020. http://dx.doi.org/10.1364/sppcom.2020.spw1i.3.

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Кутепов, Илья, Ilya Kutepov, Вадим Крысько, et al. "Complexity of EEG Signals in Schizophrenia Syndromes." In 29th International Conference on Computer Graphics, Image Processing and Computer Vision, Visualization Systems and the Virtual Environment GraphiCon'2019. Bryansk State Technical University, 2019. http://dx.doi.org/10.30987/graphicon-2019-2-140-143.

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In the present study, 45 patients with schizophrenia syndromes and 39 healthy subjects are studied with electroencephalogram (EEG) signals. The study groups were of different genders. For each of the two groups, the signals were analyzed using 16 EEG channels. Multiscale entropy, Lempel-Ziv complexity and Lyapunov exponent were used to study the chaotic signals. The data were compared for two groups of subjects. Entropy was compared for each of the 16 channels for all subjects. As a result, topographic images of brain areas were obtained, illustrating the entropy and complexity of Lempel-Ziv.
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Reports on the topic "Signal complexity"

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Crispin, Darla. Artistic Research as a Process of Unfolding. Norges Musikkhøgskole, 2018. http://dx.doi.org/10.22501/nmh-ar.503395.

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As artistic research work in various disciplines and national contexts continues to develop, the diversity of approaches to the field becomes ever more apparent. This is to be welcomed, because it keeps alive ideas of plurality and complexity at a particular time in history when the gross oversimplifications and obfuscations of political discourses are compromising the nature of language itself, leading to what several commentators have already called ‘a post-truth’ world. In this brutal environment where ‘information’ is uncoupled from reality and validated only by how loudly and often it is
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African Open Science Platform Part 1: Landscape Study. Academy of Science of South Africa (ASSAf), 2019. http://dx.doi.org/10.17159/assaf.2019/0047.

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This report maps the African landscape of Open Science – with a focus on Open Data as a sub-set of Open Science. Data to inform the landscape study were collected through a variety of methods, including surveys, desk research, engagement with a community of practice, networking with stakeholders, participation in conferences, case study presentations, and workshops hosted. Although the majority of African countries (35 of 54) demonstrates commitment to science through its investment in research and development (R&amp;D), academies of science, ministries of science and technology, policies, rec
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