Relevant bibliographies by topics / Signal analysis

Academic literature on the topic 'Signal analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 June 2024

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 'Signal analysis.'

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 "Signal analysis"

1

Gudiškis, Andrius. "HEART BEAT DETECTION IN NOISY ECG SIGNALS USING STATISTICAL ANALYSIS OF THE AUTOMATICALLY DETECTED ANNOTATIONS / ŠIRDIES DŪŽIŲ NUSTATYMAS IŠ IŠKRAIPYTŲ EKG SIGNALŲ ATLIEKANT AUTOMATIŠKAI APTIKTŲ ATSKAITŲ STATISTINĘ ANALIZĘ." Mokslas – Lietuvos ateitis 7, no. 3 (July 13, 2015): 300–303. http://dx.doi.org/10.3846/mla.2015.787.

Full text
Abstract:
This paper proposes an algorithm to reduce the noise distortion influence in heartbeat annotation detection in electrocardiogram (ECG) signals. Boundary estimation module is based on energy detector. Heartbeat detection is usually performed by QRS detectors that are able to find QRS regions in a ECG signal that are a direct representation of a heartbeat. However, QRS performs as intended only in cases where ECG signals have high signal to noise ratio, when there are more noticeable signal distortion detectors accuracy decreases. Proposed algorithm uses additional data, taken from arterial blood pressure signal which was recorded in parallel to ECG signal, and uses it to support the QRS detection process in distorted signal areas. Proposed algorithm performs as well as classical QRS detectors in cases where signal to noise ratio is high, compared to the heartbeat annotations provided by experts. In signals with considerably lower signal to noise ratio proposed algorithm improved the detection accuracy to up to 6%. Širdies ritmas yra vienas svarbiausių ir daugiausia informacijos apie pacientų būklę teikiančių fiziologinių parametrų. Širdies ritmas nustatomas iš elektrokardiogramos (EKG), atliekant QRS regionų, kurie yra interpretuojami kaip širdies dūžio ãtskaitos, paiešką. QRS regionų aptikimas yra klasikinis uždavinys, nagrinėjamas jau keletą dešimtmečių, todėl širdies dūžių nustatymo iš EKG signalų metodų yra labai daug. Deja, šie metodai tikslūs ir patikimi tik esant dideliam signalo ir triukšmo santykiui. Kai EKG signalai labai iškraipomi, QRS aptiktuvai ne visada gali atskirti QRS regioną, o kartais jį randa ten, kur iš tikro jo būti neturėtų. Straipsnyje siūlomas algoritmas, kurį taikant sumažinama triukšmo įtaka nustatant iš EKG signalų QRS regionus. Tam naudojamas QRS aptiktuvas, kartu prognozuojantis širdies dūžio atskaitą. Remiamasi arterinio kraujo spaudimo signalo duomenimis, renkama atskaitų statistika ir atliekama jos analizė.
APA, Harvard, Vancouver, ISO, and other styles
2

Debbal, S. M. "Pathological Electromyogram (EMG) Signal Analysis Parameters." Clinical Cardiology and Cardiovascular Interventions 4, no. 13 (August 9, 2021): 01–14. http://dx.doi.org/10.31579/2641-0419/185.

Full text
Abstract:
Clinical analysis of the electromyogram is a powerful tool for diagnosis of neuromuscular diseases. There fore, the detection and the analysis of electromyogram signals has he attracted much attention over the years. Several methods based on modern signal Processing techniques such as temporal analysis, spectro-temporel analysis ..., have been investigated for electromyogram signal treatment. However, many of these analysis methods are not highly successful due to their complexity and non-stationarity. The aim of this study is to analyse the EMGs signals using nonlinear analysis. This analysis can provide a wide range of information’s related to the type of signal (normal and pathological).
APA, Harvard, Vancouver, ISO, and other styles
3

Linh, Vuong Thuy, Nguyen Van Vu, and Le Ngoc Giang. "Voice Signal Quality Assessment Based on Signal Quality Standards and Analysis." International Journal of Research Publication and Reviews 4, no. 6 (June 2023): 958–63. http://dx.doi.org/10.55248/gengpi.4.623.44854.

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

HORIHATA, SATOSHI, ZHONG ZHANG, TAKASHI IMAMURA, TETSUO MIYAKE, HIROSHI TODA, and YOSHIFUMI YASUDA. "BIOLOGICAL SIGNAL ANALYSIS BY INDEPENDENT COMPONENT ANALYSIS USING COMPLEX WAVELET TRANSFORM." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 04 (July 2010): 595–608. http://dx.doi.org/10.1142/s0219691310003663.

Full text
Abstract:
Independent component analysis (ICA) is a useful method for blind source separation of two or more signals. We have previously proposed a new method combining ICA with the complex discrete wavelet transform (CDWT), in which voice and noise signals were separated using a new method. At that time, we used a simulated signal. In this study, we analyze measured biological signals by using a new method, and discuss its effectiveness. As an experiment, we try to separate an electromyogram (EMG) signal from an electrocardiogram (ECG) signal.
APA, Harvard, Vancouver, ISO, and other styles
5

B. Raveendranadh Singh, B. Raveendranadh Singh, Kanchan Sanalkar, and D. Chenna Kesavaiah. "Electrocardiograph (ECG) Signal Analysis by Neural Networks." International Journal of Scientific Research 2, no. 7 (June 1, 2012): 191–95. http://dx.doi.org/10.15373/22778179/july2013/63.

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

M, Sankar, Narendra Babu J, Swati S. Halunde, and Maduri B. Mulik. "Brain Signal Processing: Analysis, Technologies and Application." Journal of Advanced Research in Dynamical and Control Systems 11, no. 12 (December 20, 2019): 69–74. http://dx.doi.org/10.5373/jardcs/v11i12/20193213.

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

Mitraković, D., I. Grabec, and S. Sedmak. "Simulation of AE signals and signal analysis systems." Ultrasonics 23, no. 5 (September 1985): 227–32. http://dx.doi.org/10.1016/0041-624x(85)90018-6.

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

Chandrasekaran, R., R. J. Hemalath, E. Anand Kumar, S. Murali, T. R. Thamizhvani, and Soumya Y.K. "Spectral analysis of polysomnography." International Journal of Engineering & Technology 7, no. 2.25 (May 3, 2018): 86. http://dx.doi.org/10.14419/ijet.v7i2.25.16565.

Full text
Abstract:
The Polysomnography (PSG) is the most commonly used test in the diagnosis of OSAS – Obstructive Sleep Apnea Syndrome. PSG signals consist of simultaneous recording of multiple physiological parameters related to sleep and wakefulness. PSG is used to evaluate abnormalities of sleep and or wakefulness and other physiological disorders that have an impact on or related to sleep and or wakefulness. In this paper, we propped an idea of detection of insomnia based on frequency spectral analysis of PSG signals. The PSG signals consist of EMG of the chin, EEG taken from various lobes, respiratory signal, EOG signals, Temporary rectal signal and ECG signal. From all these physiological parameters, the Spectral analysis of EOG (horizontal), EEG FPZ-CZ and PZ-OZ [EEG 10-20 electrodes paced on midline FPZ,CZ,OZ channels]signals are analyzed and the mean, variance, standard deviation, RMS value and SNR features of the signal are extracted. The proposed methodology is applied to the male as well as female subjects at the age group of 30-40 years. The difference of the frequency range taken at respective intervals of time is noted and compared.
APA, Harvard, Vancouver, ISO, and other styles
9

Zhang, Xin, Feng Tian, Cai Hua Li, Guang Fu Sun, and Gang Ou. "Configurable Modernized Navigation Signal Generation Method and Performance Analysis." Applied Mechanics and Materials 333-335 (July 2013): 711–17. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.711.

Full text
Abstract:
In order to provide higher accuracy performance in navigation and positioning requirements, modernized navigation signals with more complex structure, such as MBOC or AltBOC signal, have been actively researched and used in the modernized GPS system, like emerging Galileo and BD-2 system. For the navigation signal simulator which generates those modernized signals, traditional bipolar BPSK or QPSK signal generation method cannot permit to generate those multi-level signals successfully and different modernized signals flexibly. After analyzing the current public modernized signal structure, a novel configurable signal generation method for generating the modernized navigation signal has been proposed. The amplitude quantization word-length and phase truncation error of the LUT (look-up table) used by the method have been analyzed. Experimental simulation results demonstrate the correctness and efficiency of this new method.
APA, Harvard, Vancouver, ISO, and other styles
10

Evans, David H. "Doppler signal analysis." Ultrasound in Medicine & Biology 26 (May 2000): S13—S15. http://dx.doi.org/10.1016/s0301-5629(00)00153-8.

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

Dissertations / Theses on the topic "Signal analysis"

1

Haghighi-Mood, Ali. "Analysis of phonocardiographic signals using advanced signal processing techniques." Thesis, University of Sussex, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321465.

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

Mishin, A. "Biomagnetic signal analysis." Thesis, Swansea University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.638202.

Full text
Abstract:
Most of this thesis is an account of the effort to develop new methods for biomagnetic data analysis. Variations of the heart rate reflect the neural heart control mechanisms which are performed via the electrical modulation of the sinoatrial node by the autonomic nervous system. This modulation involves the interaction of several physiological mechanisms that operate on differing time scales. Using SQUID (superconducting quantum interference device) instrumentation, the fetal cardiogram can be measured with great accuracy and a high temporal resolution, thereby providing the opportunity to assess the neural function in the fetus non-invasively by analysing heart rate variability (HRV). However, a quantitative analysis of HRV requires several other physiological parameters such as blood pressure, respiration etc. to be analysed simultaneously with HRV. These parameters are obviously inaccessible in the fetus although they are routinely recorded in premature neonates treated in the intensive care units. Using a time domain correlation method, the behaviour of different HRV components was quantitatively studied for both fetuses and premature neonates and a number of consistent features were found. The correlation between neonatal HRV, respiration and arterial blood pressure was studied with the ultimate goal of constructing a numerical model of HRV. It was also observed that different types of ventilation equipment used in neonatal intensive care cause different patterns of respiration/HRV correlation, which may be indicative of the efficacy of the ventilator. Investigation of the spontaneous activity of the human brain and in particular alpha rhythm is another area where SQUID-based biomagnetic techniques can make an important contribution. In the final chapter of this work the multichannel alpha magnetoencephalogram (MEG) is considered as a sequences of MEG maps. A neural-net based algorithm for segmentation of MEG records into words is presented. Using this method three recurring words were found in an eight-second magnetoecephalogram. This could be of value for active testing of the functional role of the cortex in neurological experiments.
APA, Harvard, Vancouver, ISO, and other styles
3

Vaizurs, Raja Sarath Chandra Prasad. "Atrial Fibrillation Signal Analysis." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3386.

Full text
Abstract:
Atrial fibrillation (AF) is the most common type of cardiac arrhythmia encountered in clinical practice and is associated with an increased mortality and morbidity. Identification of the sources of AF has been a goal of researchers for over 20 years. Current treatment procedures such as Cardio version, Radio Frequency Ablation, and multiple drugs have reduced the incidence of AF. Nevertheless, the success rate of these treatments is only 35-40% of the AF patients as they have limited effect in maintaining the patient in normal sinus rhythm. The problem stems from the fact that there are no methods developed to analyze the electrical activity generated by the cardiac cells during AF and to detect the aberrant atrial tissue that triggers it. In clinical practice, the sources triggering AF are generally expected to be at one of the four pulmonary veins in the left atrium. Classifying the signals originated from four pulmonary veins in left atrium has been the mainstay of signal analysis in this thesis which ultimately leads to correctly locating the source triggering AF. Unlike many of the current researchers where they use ECG signals for AF signal analysis, we collect intra cardiac signals along with ECG signals for AF analysis. AF Signal collected from catheters placed inside the heart gives us a better understanding of AF characteristics compared to the ECG. . In recent years, mechanisms leading to AF induction have begun to be explored but the current state of research and diagnosis of AF is mainly about the inspection of 12 lead ECG, QRS subtraction methods, spectral analysis to find the fibrillation rate and limited to establishment of its presence or absence. The main goal of this thesis research is to develop methodology and algorithm for finding the source of AF. Pattern recognition techniques were used to classify the AF signals originated from the four pulmonary veins. The classification of AF signals recorded by a stationary intra-cardiac catheter was done based on dominant frequency, frequency distribution and normalized power. Principal Component Analysis was used to reduce the dimensionality and further, Linear Discriminant Analysis was used as a classification technique. An algorithm has been developed and tested during recorded periods of AF with promising results.
APA, Harvard, Vancouver, ISO, and other styles
4

Ajayi, A. A. "Turbine flowmeter signal analysis." Thesis, University of Bradford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.381420.

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

Krishnan, Sridhar. "Adaptive signal processing techniques for analysis of knee joint vibroarthrographic signals." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0016/NQ47897.pdf.

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

Alsop, Stephen A. "Defeating signal analysis aliasing problems." Thesis, University of Strathclyde, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248868.

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

Bienvenu, Kirk Jr. "Underwater Acoustic Signal Analysis Toolkit." ScholarWorks@UNO, 2017. https://scholarworks.uno.edu/td/2398.

Full text
Abstract:
This project started early in the summer of 2016 when it became evident there was a need for an effective and efficient signal analysis toolkit for the Littoral Acoustic Demonstration Center Gulf Ecological Monitoring and Modeling (LADC-GEMM) Research Consortium. LADC-GEMM collected underwater acoustic data in the northern Gulf of Mexico during the summer of 2015 using Environmental Acoustic Recording Systems (EARS) buoys. Much of the visualization of data was handled through short scripts and executed through terminal commands, each time requiring the data to be loaded into memory and parameters to be fed through arguments. The vision was to develop a graphical user interface (GUI) that would increase the productivity of manual signal analysis. It has been expanded to make several calculations autonomously for cataloging and meta data storage of whale clicks. Over the last year and a half, a working prototype has been developed with MathWorks matrix laboratory (MATLAB), an integrated development environment (IDE). The prototype is now very modular and can accept new tools relatively quickly when development is completed. The program has been named Banshee, as the mythical creatures are known to “wail”. This paper outlines the functionality of the GUI, explains the benefits of frequency analysis, the physical models that facilitate these analytics, and the mathematics performed to achieve these models.
APA, Harvard, Vancouver, ISO, and other styles
8

Lei, Chi-un, and 李志遠. "VLSI macromodeling and signal integrity analysis via digital signal processing techniques." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B45700588.

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

Ashraf, Pouya, Linnar Billman, and Adam Wendelin. "Teaching Signals to Students: a Tool for Visualizing Signal, Filter and DSP Concepts." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297168.

Full text
Abstract:
Students at Uppsala University have for some years been given the opportunity to take courses in subjects directly, or indirectly, related to the fields of signal processing and signal analysis. According to the directors of these courses, a considerable number of students are recurringly having difficulties grasping different concepts related to this field of study. This report covers a tool that easily allows teachers to visualize and listen to different manipulations of signals, which should help students get an intuitive understanding of the subject. Features of the system include multiple kinds of analog filters, sampling with variable settings and zero-order hold reconstruction. The finished system is flexible, tunable and modifiable to the teachers every need, making it usable for a wide variety of courses involving signal processing. The system meets its requirements even though individual components’ results de- viate slightly from ideal values.
Studenter vid Uppsala Universitet har, under ett antal år, givits möjligheten att läsa kurser inom ämnen direkt, eller indirekt, relaterade till signalbehandling/signalanalys. Enligt kursansvariga för dessa kurser har en ansenlig andel av studenterna svårigheter med att förstå en del av de begrepp och fenomen som förekommer under kurserna. Denna rapport behandlar ett verktyg som ger lärare i dessa kurser möjlighet att på ett enkelt sätt visualisera och lyssna på olika manipulationer av signaler, vilket bör hjälpa studenterna bygga en intuition för ämnet. Systemets olika funktioner inkluderar flera olika typer av analoga filter, sampling med olika inställningar, och så kallad ’Zero-Order-Hold’ rekonstruktion. Det resulterande systemet är flexibelt, inställbart och modifierbart till användarens behov, vilket gör det applicerbart i flera kurser som innefattar signalbehandling/analys. Systemet möter kraven som ställs, även fast resultaten hos individuella komponenter avviker aningen från ideala värden.
APA, Harvard, Vancouver, ISO, and other styles
10

Purahoo, K. "Maximum entropy data analysis." Thesis, Cranfield University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260038.

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

Books on the topic "Signal analysis"

1

Robinson, Enders A. Geophysical signal analysis. Tulsa, Okla: Society of Exploration Geophysicists, 2000.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Elgendi, Mohamed. PPG Signal Analysis. Boca Raton : Taylor & Francis, [2018]: CRC Press, 2020. http://dx.doi.org/10.1201/9780429449581.

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

Rangayyan, Rangaraj M., ed. Biomedical Signal Analysis. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119068129.

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

1958-, Hush Don R., ed. Digital signal analysis. 2nd ed. Englewood Cliffs, N.J: Prentice-Hall, 1990.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

1958-, Hush Don R., ed. Digital signal analysis. 2nd ed. Englewood Cliffs, N.J: Prentice Hall, 1990.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Stearns, Samuel D. Digitale Verarbeitung analoger Signale: Digital signal analysis. 4th ed. München: R. Oldenbourg, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

N, Rutledge D., ed. Signal treatment and signal analysis in NMR. New York: Elsevier Science, 1996.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

1948-, Procházka A., ed. Signal analysis and prediction. Boston: Birkhauser, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Garello, René, ed. Two-Dimensional Signal Analysis. London, UK: ISTE, 2008. http://dx.doi.org/10.1002/9780470611067.

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

Procházka, Ales, Jan Uhlíř, P. W. J. Rayner, and N. G. Kingsbury, eds. Signal Analysis and Prediction. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-1768-8.

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

Book chapters on the topic "Signal analysis"

1

Auger, François. "Signal Analysis." In Signal Processing with Free Software, 13–25. Hoboken, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118579619.ch2.

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

Wu, Yunfeng. "Signal Analysis." In Knee Joint Vibroarthrographic Signal Processing and Analysis, 33–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44284-5_3.

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

Albertos, Pedro, and Iven Mareels. "Signal Analysis." In Feedback and Control for Everyone, 87–112. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-03446-6_4.

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

Alencar, Marcelo S., and Valdemar C. da Rocha. "Signal Analysis." In Communication Systems, 1–39. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12067-1_1.

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

Ortolani, Claudio. "Signal Analysis." In Flow Cytometry Today, 121–35. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10836-5_8.

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

de Alencar, Marcelo Sampaio. "Signal Analysis." In Music Science, 47–60. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003338895-4.

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

Weik, Martin H. "signal analysis." In Computer Science and Communications Dictionary, 1577. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_17338.

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

Alencar, Marcelo S., and Valdemar C. da Rocha. "Signal Analysis." In Communication Systems, 1–35. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25462-9_1.

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

Doghmane, Mohamed Zinelabidine, Sid-Ali Ouadfeul, and Leila Aliouane. "Signal Analysis." In Encyclopedia of Mathematical Geosciences, 1–10. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_289-1.

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

Doghmane, Mohamed Zinelabidine, Sid-Ali Ouadfeul, and Leila Aliouane. "Signal Analysis." In Encyclopedia of Mathematical Geosciences, 1288–97. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-85040-1_289.

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

Conference papers on the topic "Signal analysis"

1

Wu, J. B., J. Chen, Z. M. Zhong, and P. Zhong. "Application of Blind Source Separation Method in Mechanical Sound Signal Analysis." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-39225.

Full text
Abstract:
As the result of vibration emission in air, the mechanical noise signal carries affluent information about the working condition of machinery and it can be used in mechanical fault diagnosis. But in practice, the measured sound signal is usually the mixing of condition signal and other uncorrelated signals. And the signal received is usually of very low SNR. Therefore, to obtain the features of original signals, the mixed signals have to be separated and the uncorrelated signals have to be removed by means of the blind source separation technique. The BSS is a class of signal processing method that can recover the original signals according to the observed mixing signals. In application of BSS algorithms, it is generally supposed that the number of sources is known. But unfortunately, this is not the case in application. Then, before applying the BSS method, the singular-value analysis method is introduced to estimate the number of sound sources at first. On the other hand, to avoid the ill-conditioned problem caused by environment noise and/or measuring noise in applying BSS method, the partial singular-value analysis method is employed to select those signals with maximum information entropy from mixed signals. This method significantly reduces the distortion of separated signals. Afterward, the second order blind identification (SOBI) algorithm, one of the BSS methods, which only relies on the second order statistics of measuring signals, is utilized and it is modified, in this paper, especially for purpose of spectra separation. Finally, the spectra separation results obtained from the mixed signals measured in a semi-anechoic chamber demonstrate the availability of the presented method.
APA, Harvard, Vancouver, ISO, and other styles
2

"ECG SIGNAL ANALYSIS." In International Conference on Research in Business management & Information Technology. ELK ASIA PACIFIC JOURNAL, 2015. http://dx.doi.org/10.16962/elkapj/si.it.icrbit-2015.30.

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

Chivukula, V. N. Aditya Datta, and Sri Keshava Reddy Adupala. "Music Signal Analysis: Regression Analysis." In 2nd International Conference on Machine Learning, IOT and Blockchain (MLIOB 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111205.

Full text
Abstract:
Machine learning techniques have become a vital part of every ongoing research in technical areas. In recent times the world has witnessed many beautiful applications of machine learning in a practical sense which amaze us in every aspect. This paper is all about whether we should always rely on deep learning techniques or is it really possible to overcome the performance of simple deep learning algorithms by simple statistical machine learning algorithms by understanding the application and processing the data so that it can help in increasing the performance of the algorithm by a notable amount. The paper mentions the importance of data pre-processing than that of the selection of the algorithm. It discusses the functions involving trigonometric, logarithmic, and exponential terms and also talks about functions that are purely trigonometric. Finally, we discuss regression analysis on music signals.
APA, Harvard, Vancouver, ISO, and other styles
4

Costea, I. M., C. I. Dumitrescu, N. Dumitru, and B. Soare. "Biomedical signals analysis techniques using the signal processor TMS320C6211B." In 2014 37th ISSE International Spring Seminar in Electronics Technology (ISSE). IEEE, 2014. http://dx.doi.org/10.1109/isse.2014.6887617.

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

Meehan, P. A., and P. A. Bellette. "Chaotic Signal Analysis of Parkinson's Disease STN Brain Signals." In Topics on Chaotic Systems - Selected Papers from CHAOS 2008 International Conference. WORLD SCIENTIFIC, 2009. http://dx.doi.org/10.1142/9789814271349_0027.

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

Tzou, H. S., D. W. Wang, and I. Hagiwara. "Distributed Dynamic Signal Analysis of Piezoelectric Laminated Linear and Nonlinear Toroidal Shells." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/ad-23715.

Full text
Abstract:
Abstract Toroidal shells belong to the shells of revolution family. Dynamic sensing signals and their distributed characteristics of spatially distributed sensors or neurons laminated on thin toroidal shell structures are investigated in this study. Spatially distributed modal voltages and signal patterns are related to the meridional and circumferential membrane/bending strains, based on the direct piezoelectricity, the Gauss theorem, the Maxwell principle and the open-circuit assumption. Linear and nonlinear toroidal shells are defined based on the thin shell theory and the von Karman geometric nonlinearity. With the simplified mode shape functions defined by the Donnell-Mushtari-Vlasov theory, modal dependent distributed signals and detailed signal components of spatially distributed sensors or neurons are defined and these signals are quantitatively illustrated. Signal distributions basically reveal distinct modal characteristics of toroidal shells. Parametric studies suggest that the dominating signal component originates from the meridional membrane strains. Shell dimensions, materials, boundary conditions, natural modes, sensor locations/distributions/sizes, modal strain components, etc. all influence the spatially distributed modal voltages and signal generations.
APA, Harvard, Vancouver, ISO, and other styles
7

Tsuei, Kuang-Yih, Wen-Wang Jiang, and Shu-Fen Kuo. "Measurement Signal Effects on the Normal-Incidence Absorption Coefficient." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58381.

Full text
Abstract:
This paper will demonstrate the signal effects on the normal-incidence absorption coefficient. The test method covers two microphones located in impedance tube to measure this coefficient. It should analyze the measurement procedure and formulae theoretically, furthermore to propose the coherence function as the criteria for measurement results. Experimentally, different signals, generated by a sound source, input to the loudspeaker in impedance tube to produce the plane wave and two microphones can measure the sound pressures. Through different time weightings and average times on the two microphone signals, and after analyzing results of the frequency response, the coherence function and the normal-incidence absorption coefficient, the coherence function is a major factor to check the normal-incidence absorption coefficient reliable, even the test system stable or not.
APA, Harvard, Vancouver, ISO, and other styles
8

"Signal Processing & Analysis." In 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus). IEEE, 2021. http://dx.doi.org/10.1109/elconrus51938.2021.9396123.

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

"Signal Processing and Analysis." In 2021 3rd International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE). IEEE, 2021. http://dx.doi.org/10.1109/reepe51337.2021.9387999.

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

Cristea, Paul Dan, Rodica Tuduce, Jan Cornelis, and Adrian Munteanu. "Nucleotide genomic signal analysis." In 2008 International Conference on Signals and Electronic Systems. IEEE, 2008. http://dx.doi.org/10.1109/icses.2008.4673398.

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

Reports on the topic "Signal analysis"

1

King-Smith, Deen, Anthony Martone, and Marc Ressler. Reflected Signal Analysis. Fort Belvoir, VA: Defense Technical Information Center, January 2010. http://dx.doi.org/10.21236/ada513228.

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

Himed, Braham. Multi-Channel Signal Generation and Analysis. Fort Belvoir, VA: Defense Technical Information Center, September 1998. http://dx.doi.org/10.21236/ada362362.

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

Steven A. Wallace. Signal Analysis for Radiation Event Identification. Office of Scientific and Technical Information (OSTI), December 2004. http://dx.doi.org/10.2172/835543.

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

Ichinose, G. LL18-Signal Analysis-NDD2Ad Final Report. Office of Scientific and Technical Information (OSTI), September 2021. http://dx.doi.org/10.2172/1832326.

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

Dodge, D. DFTT report for Signal Analysis 2023. Office of Scientific and Technical Information (OSTI), July 2023. http://dx.doi.org/10.2172/1992195.

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

Paulson, Albert S., and Gerald R. Swope. Signal Model Analysis Via Model-Critical Methods. Fort Belvoir, VA: Defense Technical Information Center, October 1988. http://dx.doi.org/10.21236/ada200685.

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

Fritzke, A., and P. Top. Signal to Noise Analysis of iRadar sensors. Office of Scientific and Technical Information (OSTI), September 2009. http://dx.doi.org/10.2172/967738.

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

Kumaresan, R. Parametric Time-Scale Methods in Signal Analysis. Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada274212.

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

Tufts, Donald W., and Brian Freburger. Naval Signal and Image Analysis Conference Report. Fort Belvoir, VA: Defense Technical Information Center, February 1998. http://dx.doi.org/10.21236/ada338285.

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

Mellinger, David K. Book: Marine Bioacoustic Signal Processing and Analysis. Fort Belvoir, VA: Defense Technical Information Center, September 2011. http://dx.doi.org/10.21236/ada598289.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Signal analysis' for particular source types:
Journal articles Dissertations / Theses Books
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