Root mean square

View this topic in
In mathematics, the root mean square (abbreviated RMS or rms), also known as the quadratic mean, is a statistical measure of the magnitude of a varying quantity. (Wikipedia.org)






Conferences related to Root mean square

Back to Top

2018 IEEE/ION Position, Location and Navigation Symposium (PLANS)

The Position Location and Navigation Symposium (PLANS) is a biennial technical conference that occurs in the spring of even numbered years. Our mission is to provide a forum to share the latest advances in navigation technology.


2018 IEEE/OES Baltic International Symposium (BALTIC)

Energy Security, Hazard Mitigation, Ammunition Disposal, Ecosystems & Socio-economic impacts, Baltic Sea


2018 International Conference on Power System Technology (POWERCON)

The conference will focus on smart grid, energy interconnection, UHV transmission, distributed generation, renewable energy generation and its integration into large grid, energy storage, energy saving and emission reduction.


2017 13th IEEE International Conference on Control & Automation (ICCA)

Theory and applications of control and automation, and possible contributions toward sustainable development and environment preservation


2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) is a premier international forum for scientists and researchers to present the state of the art of data mining and intelligent methods inspired from nature, particularly biological, linguistic, and physical systems, with applications to computers, circuits, systems, control, robotics, communications, and more.

  • 2016 12th International Conference on Natural Computation and 13th Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

    International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) is a premier international forum for scientists and researchers to present the state of the art of data mining and intelligent methods inspired from nature, particularly biological, linguistic, and physical systems, with applications to computers, circuits, systems, control, robotics, communications, and more.

  • 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

    FSKD is an international forum on fuzzy systems and knowledge discovery. Specific topics include fuzzy sets, Bioinformatics and Bio-Medical Informatics, Genomics, Proteomics, Big Data, Databases and Applications, Semi-Structured/Unstructured Data Mining, Multimedia Mining, Web and Text Data Mining, Graphic Model Discovery, Data Warehousing and OLAP, Pattern Recognition and Diagnostics, etc..

  • 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

    FSKD is an international forum on fuzzy systems and knowledge discovery. Specific topics include fuzzy sets, rough sets, Statistical methods, Parallel/ Distributed data mining, KDD Process and human interaction, Knowledge management, Knowledge visualization, Reliability and robustness, Knowledge Discovery in Specific Domains, High dimensional data, Temporal data, Data streaming, Scientific databases, Semi-structured/unstructured data, Multimedia, Text, Web and the Internet, Graphic model discovery, Software warehouse and software mining, Data engineering, Communications and networking, Software engineering, Distributed systems and computer hardware

  • 2013 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

    FSKD is an international forum on fuzzy systems and knowledge discovery. Specific topics include fuzzy sets, rough sets, Statistical methods, Parallel/ Distributed data mining, KDD Process and human interaction, Knowledge management, Knowledge visualization, Reliability and robustness, Knowledge Discovery in Specific Domains, High dimensional data, Temporal data, Data streaming, Scientific databases, Semi-structured/unstructured data, Multimedia, Text, Web and the Internet, Graphic model discovery, Software warehouse and software mining, Data engineering, Communications and networking, Software engineering, Distributed systems and computer hardware, etc.

  • 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

    FSKD is an international forum on fuzzy systems and knowledge discovery. Specific topics include fuzzy theory and foundations; stability of fuzzy systems; fuzzy methods and algorithms; fuzzy image, speech and signal processing; multimedia; fuzzy hardware and architectures; data mining.

  • 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

    FSKD is an international forum on fuzzy systems and knowledge discovery. Specific topics include fuzzy theory and foundations; stability of fuzzy systems; fuzzy methods and algorithms; fuzzy image, speech and signal processing; multimedia; fuzzy hardware and architectures; data mining.

  • 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

    FSKD is an international forum on fuzzy systems and knowledge discovery. Specific topics include fuzzy theory and foundations; stability of fuzzy systems; fuzzy methods and algorithms; fuzzy image, speech and signal processing; multimedia; fuzzy hardware and architectures; data mining.

  • 2007 International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

    FSKD '07 covers all aspects of fuzzy systems and knowledge discovery, including recent theoretical advances and interesting applications, for example, fuzzy theory and models, mathematical foundation of fuzzy systems, fuzzy image/signal processing, fuzzy control and robotics, fuzzy hardware and architectures, fuzzy systems and the internet, fuzzy optimization and modeling, fuzzy decision and support, classification, clustering, statistical methods, knowledge etc.


More Conferences

Periodicals related to Root mean square

Back to Top

Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Applied Superconductivity, IEEE Transactions on

Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems II: Express Briefs, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


Communications, IEEE Transactions on

Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...


More Periodicals


Xplore Articles related to Root mean square

Back to Top

A comprehensive analysis of multilayer channel waveguides

N. Osman; M. Koshiba; R. Kaji Journal of Lightwave Technology, 1994

Using a simple approach based on the scalar finite element method, propagation characteristics of multilayer channel waveguides are calculated. The effective index, modal field, confinement factor, far-field intensity pattern, and radiation angle of the far-field pattern (full width at half maximum intensity) for multilayer channel waveguides formed with multiple quantum well (MQW) materials and with the MQW materials replaced by ...


Thai syllable segmentation for connected speech based on energy

N. Jittiwarangkul; S. Jitapunkul; S. Luksaneeyanavin; V. Ahkuputra; C. Wutiwiwatchai IEEE. APCCAS 1998. 1998 IEEE Asia-Pacific Conference on Circuits and Systems. Microelectronics and Integrating Systems. Proceedings (Cat. No.98EX242), 1998

This paper proposes a novel technique based on local maximum and minimum energy contour to segment syllables of connected speech. Energy contour used in this technique was obtained from five energy algorithms: the absolute energy, the root mean square energy, the square energy, Teager energy and the modified Teager energy. The experimental result was conducted on 36 utterances, 11 speakers ...


Fast Recommendations With the M-Distance

Mei Zheng; Fan Min; Heng-Ru Zhang; Wen-Bin Chen IEEE Access, 2016

Memory-based recommender systems with m users and n items typically require O(mn) space to store the rating information. In item-based collaborative filtering (CF) algorithms, the feature vector of each item has length m,and it takes O(m) time to compute the similarity between two items using the Pearson or cosine distances. In this paper, we propose an efficient CF algorithm based ...


A low-noise latching comparator probe for waveform sampling applications

D. I. Bergman; B. C. Waltrip IEEE Transactions on Instrumentation and Measurement, 2003

A new latching comparator probe is described. The probe is being developed as part of an effort to augment voltage measurement capability in the 10 Hz to 1 MHz frequency range. The probe offers an input voltage range of ±10 V, input impedance of 1 MΩ and root mean square noise referred to the input as low as 55 μV. ...


Semi-Parametric Estimation in Magnetic Resonance Spectroscopy: Automation of the Disentanglement Procedure

H. Rabeson; H. Ratiney; D. van Ormondt; D. Graveron-Demilly 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007

Semi-parametric disentanglement of parametric parts from non-parametric parts of a signal is a universal problem. This study concerns estimation of metabolite concentrations from in vivo Magnetic Resonance Spectroscopy (MRS) signals. Due to in vivo conditions, so-called macro- molecules contribute non- parametric components to the signals. Disentanglement is achieved by exploiting prior knowledge about the parametric and non-parametric parts directly in ...


More Xplore Articles

Educational Resources on Root mean square

Back to Top

eLearning

A comprehensive analysis of multilayer channel waveguides

N. Osman; M. Koshiba; R. Kaji Journal of Lightwave Technology, 1994

Using a simple approach based on the scalar finite element method, propagation characteristics of multilayer channel waveguides are calculated. The effective index, modal field, confinement factor, far-field intensity pattern, and radiation angle of the far-field pattern (full width at half maximum intensity) for multilayer channel waveguides formed with multiple quantum well (MQW) materials and with the MQW materials replaced by ...


Thai syllable segmentation for connected speech based on energy

N. Jittiwarangkul; S. Jitapunkul; S. Luksaneeyanavin; V. Ahkuputra; C. Wutiwiwatchai IEEE. APCCAS 1998. 1998 IEEE Asia-Pacific Conference on Circuits and Systems. Microelectronics and Integrating Systems. Proceedings (Cat. No.98EX242), 1998

This paper proposes a novel technique based on local maximum and minimum energy contour to segment syllables of connected speech. Energy contour used in this technique was obtained from five energy algorithms: the absolute energy, the root mean square energy, the square energy, Teager energy and the modified Teager energy. The experimental result was conducted on 36 utterances, 11 speakers ...


Fast Recommendations With the M-Distance

Mei Zheng; Fan Min; Heng-Ru Zhang; Wen-Bin Chen IEEE Access, 2016

Memory-based recommender systems with m users and n items typically require O(mn) space to store the rating information. In item-based collaborative filtering (CF) algorithms, the feature vector of each item has length m,and it takes O(m) time to compute the similarity between two items using the Pearson or cosine distances. In this paper, we propose an efficient CF algorithm based ...


A low-noise latching comparator probe for waveform sampling applications

D. I. Bergman; B. C. Waltrip IEEE Transactions on Instrumentation and Measurement, 2003

A new latching comparator probe is described. The probe is being developed as part of an effort to augment voltage measurement capability in the 10 Hz to 1 MHz frequency range. The probe offers an input voltage range of ±10 V, input impedance of 1 MΩ and root mean square noise referred to the input as low as 55 μV. ...


Semi-Parametric Estimation in Magnetic Resonance Spectroscopy: Automation of the Disentanglement Procedure

H. Rabeson; H. Ratiney; D. van Ormondt; D. Graveron-Demilly 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007

Semi-parametric disentanglement of parametric parts from non-parametric parts of a signal is a universal problem. This study concerns estimation of metabolite concentrations from in vivo Magnetic Resonance Spectroscopy (MRS) signals. Due to in vivo conditions, so-called macro- molecules contribute non- parametric components to the signals. Disentanglement is achieved by exploiting prior knowledge about the parametric and non-parametric parts directly in ...


More eLearning Resources

IEEE-USA E-Books

  • Covariance, Subspace, and Intrinsic CramrRao Bounds

    Cramï¿¿r-Rao bounds on estimation accuracy are established for estimation problems on arbitrary manifolds in which no set of intrinsic coordinates exists. The frequently encountered examples of estimating either an unknown subspace or a covariance matrix are examined in detail. The set of subspaces, called the Grassmann manifold, and the set of covariance (positive-definite Hermitian) matrices have no fixed coordinate system associated with them and do not possess a vector space structure, both of which are required for deriving classical Cramï¿¿r-Rao bounds. Intrinsic versions of the Cramï¿¿r-Rao bound on manifolds utilizing an arbitrary affine connection with arbitrary geodesics are derived for both biased and unbiased estimators. In the example of covariance matrix estimation, closed-form expressions for both the intrinsic and flat bounds are derived and compared with the root-mean-square error (RMSE) of the sample covariance matrix (SCM) estimator for varying sample support K. The accuracy bound on unbiased covariance matrix estimators is shown to be about (10/log 10)n/K 1/2 dB, where n is the matrix order. Remarkably, it is shown that from an intrinsic perspective, the SCM is a biased and inefficient estimator and that the bias term reveals the dependency of estimation accuracy on sample support observed in theory and practice. The RMSE of the standard method of estimating subspaces using the singular value decomposition (SVD)is compared with the intrinsic subspace Cramï¿¿r-Rao bound derived in closed form by varying both the signal-to-noise ratio (SNR) of the unknown p-dimensional subspace and the sample support. In the simplest case, the Cramï¿¿r-Rao bound on subspace estimation accuracy is shown to be about (p(n - p)1/2 K-1/2SN-1/2 rad for p-dimensional subspaces. It is seen that the SVD-based method yields accuracies very close to the Cramï¿¿r-Rao bound, esta blishing that the principal invariant subspace of a random sample provides an excellent estimator of an unknown subspace. The analysis approach developed is directly applicable to many other estimation problems on manifolds encountered in signal processing and elsewhere, such as estimating rotation matrices in computer vision and estimating subspace basis vectors in blind source separation.

  • The Wiener RMS (Root Mean Square) Error Criterion in Filter Design and Prediction

    This chapter contains sections titled: 1 Linear Filters, 2 Minimization of RMS Error, 3 Determination of the Weighting Function, 4 Realization of Operator-- Mathematical Formulation, 5 RC Filter, 6 Prediction and Lag with and without Noise

  • Alternating Current Circuits

    This chapter contains sections titled: AC Voltage and Current Sources, Root Mean Square Values (RMS), and Power Sinusoidal Steady State: Time and Frequency Domains Time Domain Equations: Frequency Domain Impedance and Phasors Power in AC Circuits Dependent Voltage and Current Sources Summary of Key Points Further Reading Problems

  • A Fixed-Point Fast Fourier Transform Error Analysis

    This paper contains an analysis of the fixed-point accuracy of the powqer of two, fast Fourier transform algorithm. This analysis leads to approximate upper and lower bounds on the root-mean-square error. Also included are the results of some accuracy experiments on a simulated fixed-point machine and their comparison with the error upper bound.



Standards related to Root mean square

Back to Top

No standards are currently tagged "Root mean square"


Jobs related to Root mean square

Back to Top