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Relevant bibliographies by topics / Signal processing Electric filters

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Academic literature on the topic 'Signal processing Electric filters'

Author: Grafiati

Published: 4 June 2021

Last updated: 2 February 2022

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Journal articles on the topic "Signal processing Electric filters"

1

Smolarik, Lukas, Dusan Mudroncik, and Lubos Ondriga. "ECG Signal Processing." Advanced Materials Research 749 (August 2013): 394–400. http://dx.doi.org/10.4028/www.scientific.net/amr.749.394.

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Electrocardiography (ECG) is a diagnostic method that allows sensing and record the electric activity of heart [. The measurement of electrical activity is used as a standard twelve-point system. At each of these leads to measure the useful signal and interference was measured. The intensity of interference depends on the artefacts (electrical lines, brum, motion artefacts, muscle, interference from the environment, etc.). For correct evaluation of measured signal there is a need to processing the measured signal to suitable form. At present, the use of electrocardiograms with sensors with con

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Gadsden, S. A., M. Al-Shabi, and S. R. Habibi. "Estimation Strategies for the Condition Monitoring of a Battery System in a Hybrid Electric Vehicle." ISRN Signal Processing 2011 (April 13, 2011): 1–17. http://dx.doi.org/10.5402/2011/120351.

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This paper discusses the application of condition monitoring to a battery system used in a hybrid electric vehicle (HEV). Battery condition management systems (BCMSs) are employed to ensure the safe, efficient, and reliable operation of a battery, ultimately to guarantee the availability of electric power. This is critical for the case of the HEV to ensure greater overall energy efficiency and the availability of reliable electrical supply. This paper considers the use of state and parameter estimation techniques for the condition monitoring of batteries. A comparative study is presented in wh

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HAAVISTO, P., M. GABBOUJ, and Y. NEUVO. "MEDIAN BASED IDEMPOTENT FILTERS." Journal of Circuits, Systems and Computers 01, no. 02 (1991): 125–48. http://dx.doi.org/10.1142/s0218126691000021.

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Idempotent filters produce a root signal in a single filter pass, i.e. the filter output is invariant to further filterings with the same filter. In this paper median based idempotent filter structures are introduced. Two approaches to generate these filters are studied: weighted median filters and median filter cascades. Two subclasses of n-dimensional idempotent weighted median filters, called Class 1 and Class 2 filters in the paper, are introduced. It is shown that both Class 1 and Class 2 filters suppress impulsive noise from n-dimensional input signals and yet have almost no effect on th

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Vydmysh, Andriy, Oleksandr Voznyak, Igor Kupchuk, and Dmitry Boyko. "RESEARCH OF MEDIAN FILTERING OF ONE-DIMENSIONAL SIGNALS." Vibrations in engineering and technology, no. 1(96) (August 27, 2020): 88–102. http://dx.doi.org/10.37128/2306-8744-2020-1-10.

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This paper considers the principles of digital signal processing, the general provisions of digital filtering, existing methods of noise filtering in electrical signals, the median filters of one-dimensional signals are studied in detail. To solve this problem, the classification of digital signal processing tools is presented. Since the most effective for filtering noise in electrical signals are digital filters, they are given the most attention. The main purpose of signal filtering is the need to extract the information contained in them. This information, which is usually present in the am

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Chhavi Saxena, Dr, Dr Avinash Sharma, Dr Rahul Srivastav, and Dr Hemant Kumar Gupta. "Denoising of Ecg Signals Using Fir & Iir Filter: a Performance Analysis." International Journal of Engineering & Technology 7, no. 4.12 (2018): 1. http://dx.doi.org/10.14419/ijet.v7i4.12.20982.

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Electrocardiogram (ECG) signal is the electrical recording of coronary heart activity. It is a common routine and vital cardiac diagnostic tool in which in electric signals are measured and recorded to recognize the practical status of heart, but ECG signal can be distorted with noise as, numerous artifacts corrupt the unique ECG signal and decreases it quality. Consequently, there may be a need to eliminate such artifacts from the authentic signal and enhance its quality for better interpretation. ECG signals are very low frequency signals of approximately 0.5Hz-100Hz and digital filters are

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Stewart, R. W., J. J. Soraghan, and T. S. Durrani. "Noncanonical FIR filters and adaptive signal processing." Electronics Letters 25, no. 6 (1989): 414. http://dx.doi.org/10.1049/el:19890285.

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Ruiz-Alzola, J., C. Alberola-López, and C. F. Westin. "Kriging filters for multidimensional signal processing." Signal Processing 85, no. 2 (2005): 413–39. http://dx.doi.org/10.1016/j.sigpro.2004.09.009.

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Terrell, T. J. "Book Review: Digital Filters and Signal Processing." International Journal of Electrical Engineering & Education 24, no. 1 (1987): 86. http://dx.doi.org/10.1177/002072098702400123.

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Havlicek, J. P., G. R. Katz, and J. C. McKeeman. "Even length median filters in optimal signal processing." Electronics Letters 28, no. 13 (1992): 1258. http://dx.doi.org/10.1049/el:19920795.

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Morency, Matthew W., and Geert Leus. "Graphon Filters: Graph Signal Processing in the Limit." IEEE Transactions on Signal Processing 69 (2021): 1740–54. http://dx.doi.org/10.1109/tsp.2021.3061575.

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Dissertations / Theses on the topic "Signal processing Electric filters"

1

Orcutt, Edward Kerry 1964. "Correlation filters for time domain signal processing." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277215.

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This study proposes employing new filters in various configurations for use in digital communication systems. We believe that significant improvements in such performance areas as transmission rate and synchronization may be achieved by incorporating these filters into digital communications receivers. Recently reported in the literature, these filters may offer advantages over the matched filter which allow enhancements in data rates, ISI tolerance, and synchronization. To make full use of the benefits of these filters, we introduce the concept of parallel signal transmission over a single ch

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Tsim, Man-tat Jimmy. "High speed realisation of digital filters /." [Hong Kong] : University of Hong Kong, 1989. http://sunzi.lib.hku.hk/hkuto/record.jsp?B12374088.

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Law, Ying Man. "Iterative algorithms for the constrained design of filters and filter banks /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202004%20LAW.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004.<br>Includes bibliographical references (leaves 108-111). Also available in electronic version. Access restricted to campus users.

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Wepman, Jeffery Alan. "THE MODELING AND ANALYSIS OF AN AUTOMATICALLY TUNED FILTER." Thesis, The University of Arizona, 1985. http://hdl.handle.net/10150/275276.

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詹文達 and Man-tat Jimmy Tsim. "High speed realisation of digital filters." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31208939.

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Li, Min. "Induced norm optimal multirate filter bank design using LMI constraints /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202002%20LI.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002.<br>Includes bibliographical references (leaves 55-58). Also available in electronic version. Access restricted to campus users.

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Van, Duyne Scott A. "Digital filter applications to modeling wave propagation in springs, strings, membranes and acoustical space /." May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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Kwan, Wai Ming Hercule. "Parallel implementation of a fast third-order volterra digital filter /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Karam, Lina J. "Design of complex digital FIR filters in the chebyshev sense." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/22219.

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Luo, Yi. "Theory and design of M-channel cosine modulated filter banks and wavelets /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19471130.

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Books on the topic "Signal processing Electric filters"

1

Thomas, H. Michael. Analog signal processing. Simon & Schuster Custom Pub., 1991.

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Signal processing design techniques. TAB Professional and Reference Books, 1986.

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Digital filters and signal processing. Kluwer Academic Publishers, 1986.

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Digital filters and signal processing. 2nd ed. Kluwer Academic Publishers, 1989.

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Kunt, M. Digital signal processing. Artech House, 1986.

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Kunt, M. Digital signal processing. Artech House, 1986.

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Hamdy, Nadder A. Applied signal processing: Concepts, circuits, and systems. Taylor & Francis, 2008.

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8

Najim, Mohamed. Modeling, estimation and optimal filtration in signal processing. ISTE ; J. Wiley & Sons, 2008.

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9

Chirlian, Paul M. Signals and filters. Van Nostrand Reinhold, 1994.

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10

Design and analysis of analog filters: A signal processing perspective. Kluwer Academic Publishers, 2001.

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Book chapters on the topic "Signal processing Electric filters"

1

Simonik, Petr, and Pavel Brandstetter. "Signal Processing for Active Power Filters." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25646-2_74.

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

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Terrell, Trevor J., and Lik-Kwan Shark. "Digital Filters." In Digital Signal Processing. Macmillan Education UK, 1996. http://dx.doi.org/10.1007/978-1-349-13735-0_4.

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Mulgrew, Bernard, Peter Grant, and John Thompson. "Adaptive filters." In Digital Signal Processing. Macmillan Education UK, 1999. http://dx.doi.org/10.1007/978-1-349-14944-5_8.

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Rao, K. Deergha, and M. N. S. Swamy. "Adaptive Digital Filters." In Digital Signal Processing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8081-4_11.

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Alexander, S. Thomas. "Fast Transversal Filters." In Adaptive Signal Processing. Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4612-4978-8_11.

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Plataniotis, Konstantinos N., and Anastasios N. Venetsanopoulos. "Adaptive Image Filters." In Digital Signal Processing. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04186-4_3.

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Sundararajan, D. "Infinite Impulse Response Filters." In Digital Signal Processing. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-62368-5_7.

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Sundararajan, D. "Finite Impulse Response Filters." In Digital Signal Processing. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-62368-5_6.

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Bjor, Ole-Herman. "Filters." In Handbook of Signal Processing in Acoustics. Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-30441-0_7.

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Conference papers on the topic "Signal processing Electric filters"

1

Lin, L., C. T. C. Nguyen, R. T. Howe, and A. P. Pisano. "Microelectromechanical filters for signal processing." In [1992] Proceedings IEEE Micro Electro Mechanical Systems. IEEE, 1992. http://dx.doi.org/10.1109/memsys.1992.187722.

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Wang, Cheng, Chuanxue Song, and Jianhua Li. "A federated filter design of electronic stability control for electric-wheel vehicle." In 2015 8th International Congress on Image and Signal Processing (CISP). IEEE, 2015. http://dx.doi.org/10.1109/cisp.2015.7408045.

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Liye, Zhao, and Li Hongsheng. "Adaptive morphological wavelet filter used in gravimeter signal processing." In 2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC). IEEE, 2011. http://dx.doi.org/10.1109/mec.2011.6026008.

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Warman, Rahmat Aditya, Sunu Wibirama, and Agus Bejo. "Performance comparison of signal processing filters on smooth pursuit eye movements." In 2017 2nd International Conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE). IEEE, 2017. http://dx.doi.org/10.1109/icitisee.2017.8285477.

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Asif, Amir, Arash Mohammadi, and Shivam Saxena. "Reduced order distributed particle filter for electric power grids." In ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2014. http://dx.doi.org/10.1109/icassp.2014.6855080.

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Dewasthale, Mugdha M., and R. D. Kharadkar. "Acoustic Noise Cancellation Using Adaptive Filters: A Survey." In 2014 International Conference on Electronic Systems, Signal Processing and Computing Technologies (ICESC). IEEE, 2014. http://dx.doi.org/10.1109/icesc.2014.11.

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Dean, Robert, George Flowers, Nicole Sanders, et al. "Damping control of micromachined lowpass mechanical vibration isolation filters using electrostatic actuation with electronic signal processing." In Smart Structures and Materials, edited by Kon-Well Wang. SPIE, 2005. http://dx.doi.org/10.1117/12.599946.

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Altay, Yeldos A., and Artem S. Kremlev. "Signal-to-Noise Ratio and Mean Square Error Improving Algorithms Based on Newton Filters for Measurement ECG Data Processing." In 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus). IEEE, 2021. http://dx.doi.org/10.1109/elconrus51938.2021.9396391.

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Park, Simon S., and Y. Altintas. "Dynamic Compensation of Cutting Forces Measured From the Spindle Integrated Force Sensor System." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32037.

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This paper presents a dynamically compensated Spindle Integrated Force Sensor (SIFS) system to measure cutting forces. Piezo-electric force sensors are integrated to the stationary spindle housing. The structural dynamic model between the cutting forces acting on the tool tip and the measured forces at the spindle housing is identified. The system is first calibrated to compensate the influence of spindle run-out and unbalance at different speeds. Using both the cutting force and acceleration sensor signals measured at the spindle housing, a Kalman Filter is designed to filter the influence of

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Baala Sundaram, Divaakar Siva, Anoushka Kapoor, Jackie Xie, et al. "Comparison of Multiscale Frequency Characteristics of Normal Phonocardiogram With Diseased Heart States." In 2020 Design of Medical Devices Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/dmd2020-9090.

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Abstract Phonocardiogram (PCG) signals are electrical recording of heart sounds containing vital information of diagnostic importance. Several signal processing methods exist to characterize PCG, however suffers in terms of sensitivity and specificity in accurately discriminating normal and abnormal heart sounds. Recently, a multiscale frequency (MSF) analysis of normal PCG was reported to characterize subtle frequency content changes in PCG which can aid in differentiating normal and abnormal heart sounds. In this work, it was hypothesized that MSF can discriminate normal PCG signal compared

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