Conferences related to Mean square error methods

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2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


ICC 2021 - IEEE International Conference on Communications

IEEE ICC is one of the two flagship IEEE conferences in the field of communications; Montreal is to host this conference in 2021. Each annual IEEE ICC conference typically attracts approximately 1,500-2,000 attendees, and will present over 1,000 research works over its duration. As well as being an opportunity to share pioneering research ideas and developments, the conference is also an excellent networking and publicity event, giving the opportunity for businesses and clients to link together, and presenting the scope for companies to publicize themselves and their products among the leaders of communications industries from all over the world.


2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting

The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2018 will be the 15th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2018 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2017 will be the 14th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2017 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forumfor the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2016 willbe the thirteenth meeting in this series. The previous meetings have played a leading role in facilitatinginteraction between researchers in medical and biological imaging. The 2016 meeting will continue thistradition of fostering crossfertilization among different imaging communities and contributing to an integrativeapproach to biomedical imaging across all scales of observation.

  • 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2015 will be the 12th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2014 will be the eleventh meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)

    To serve the biological, biomedical, bioengineering, bioimaging and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI 2010)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2009 IEEE 6th International Symposium on Biomedical Imaging (ISBI 2009)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2008 IEEE 5th International Symposium on Biomedical Imaging (ISBI 2008)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2007 IEEE 4th International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2007)

  • 2006 IEEE 3rd International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2006)

  • 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2004)

  • 2002 1st IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2002)


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Periodicals related to Mean square error methods

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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


Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


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.


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Most published Xplore authors for Mean square error methods

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Xplore Articles related to Mean square error methods

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A novel givens rotation based fast SQR-RLS algorithm

1996 8th European Signal Processing Conference (EUSIPCO 1996), 1996

A novel Fast RLS Algorithm based on the Givens Rotation and developed from an UDU<sup>T</sup> square-root factorization of autocorrelation matrix is discussed. The algorithm presents excellent numerical properties and requires 14N multiplications and 6N divisions per sampling interval, where N is the linear filter order.


Correction to “Mean square convergence of consensus algorithms in random WSNs” [May 10 2866-2874]

IEEE Transactions on Signal Processing, 2011

In the original article named above (ibid., vol. 58, no. 5, pp. 2866-2874, May 2010), there is an error in equation (18). The corrected equation is presented here.


Upper bounds of wavelets on 2-D lipschitz class and zerotrees

2000 10th European Signal Processing Conference, 2000

The wavelet transform method has become one of the most powerful tools in image compression applications. It has a number of advantages with respect to other spectral transforms. With lossy compression, after a suitable wavelet transform is chosen two basic procedures — zonal and threshold coding — are usually applied to the spectral image [1]. In zonal coding only a ...


Prediction and filtering for random parameter systems

IRE Transactions on Information Theory, 1958

This work generalizes the Wiener-Kolmogorov theory of optimum linear filtering and prediction of stationary random inputs. It is assumed here that signal and noise have passed through a random device before being available for filtering and prediction. A random device is a unit whose behavior depends on an unknown parameter for which an a priori probability distribution is given. A ...


List of Tables

Modern HF Signal Detection and Direction Finding, None

None


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Educational Resources on Mean square error methods

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IEEE.tv Videos

Advances in Kernel Methods
Quadrotor Trajectory Tracking with L1 Optimal control
Formal Methods in Robotics
An Energy-Efficient Mixed-Signal Neuron for Inherently Error Resilient Neuromorphic Systems - IEEE Rebooting Computing 2017
The Josephson Effect: SQUIDs Then and Now: From SLUGS to Axions
Mario Milicevic - IEEE Theodore W. Hissey Outstanding Young Professional Award, 2019 IEEE Honors Ceremony
The Next G: What does 5G mean for Critical Communications and Electromagnetic Spectrum Dominance? - Manuel Uhm - 5G Technologies for Tactical and First Responder Networks 2018
IMS 2012 Microapps - Panel Session: Device Characterization Methods and Advanced RF/ Microwave Design
Robust Qubit Manipulation with Integrated Circuits: Optical Computing - Pérola Milman at INC 2019
Quantum Computation - ASC-2014 Plenary series - 4 of 13 - Tuesday 2014/8/12
IMS 2011 Microapps - Practical Methods for Estimating the Q of Spiral Inductors Using EM Planar Simulators
The Prospects for Scalable Quantum Computing with Superconducting Circuits - Applied Superconductivity Conference 2018
Learning with Kernels for Streams of Structured Data
2016 IEEE PES General Meeting: Members Meeting & Plenary Session
PELS Membership: A Powerful Advantage
Hybrid Computing for Near-term Quantum Computing Systems - Alex McCaskey - ICRC 2018
Micro-Apps 2013: Alternative Methods and Optimization Techniques for Vector Modulation
Surgical Robotics: Robotics methods for navigating untethered agents through the vascular network
IMS 2015: Chris Walker - John Tucker Special Tribute - SuperCam: A 64 Pixel SIS Receiver Array for Submillimeter-wave Astronomy
Soft, Printable, and Small: An Overview of Manufacturing Methods for Novel Robots at Harvard

IEEE-USA E-Books

  • A novel givens rotation based fast SQR-RLS algorithm

    A novel Fast RLS Algorithm based on the Givens Rotation and developed from an UDU<sup>T</sup> square-root factorization of autocorrelation matrix is discussed. The algorithm presents excellent numerical properties and requires 14N multiplications and 6N divisions per sampling interval, where N is the linear filter order.

  • Correction to “Mean square convergence of consensus algorithms in random WSNs” [May 10 2866-2874]

    In the original article named above (ibid., vol. 58, no. 5, pp. 2866-2874, May 2010), there is an error in equation (18). The corrected equation is presented here.

  • Upper bounds of wavelets on 2-D lipschitz class and zerotrees

    The wavelet transform method has become one of the most powerful tools in image compression applications. It has a number of advantages with respect to other spectral transforms. With lossy compression, after a suitable wavelet transform is chosen two basic procedures — zonal and threshold coding — are usually applied to the spectral image [1]. In zonal coding only a fixed small "zone" of transformed image is encoded and the optimal zonal coding method ensures the best selection of spectral zones at which a minimum mean-square error of reconstruction is achieved. In order to determine optimal zonal coding method for the chosen transform one has to obtain the estimates of its spectra on a given class of input images. We suggest in this paper a unified approach to obtain exact upper bounds of a given wavelet transform on the class of discrete images with bounded first order finite differences. The presented estimates allow to apriori identify the spectral "zones" that are likely to be of significance in image reconstruction for a given wavelet transform.

  • Prediction and filtering for random parameter systems

    This work generalizes the Wiener-Kolmogorov theory of optimum linear filtering and prediction of stationary random inputs. It is assumed here that signal and noise have passed through a random device before being available for filtering and prediction. A random device is a unit whose behavior depends on an unknown parameter for which an a priori probability distribution is given. A number of engineering applications are cited. Two of these are worked out in some detail to illustrate the optimization procedure.

  • List of Tables

    None

  • Total least mean squares algorithm

    Widrow (1971) proposed the least mean squares (LMS) algorithm, which has been extensively applied in adaptive signal processing and adaptive control. The LMS algorithm is based on the minimum mean squares error. On the basis of the total least mean squares error or the minimum Raleigh quotient, we propose the total least mean squares (TLMS) algorithm. The paper gives the statistical analysis for this algorithm, studies the global asymptotic convergence of this algorithm by an equivalent energy function, and evaluates the performances of this algorithm via computer simulations.

  • The adaptive least mean square algorithm using several step size for multiuser detection

    In this paper, we introduce a LMS (least mean square) algorithm with a modified step size for adaptive filtering. An adaptive feedback constant step size in the LMS algorithm controls the convergence rate of the filter coefficients but also determines the final mean-square error. Since the convergence time is inversely proportional to step size, a large step size is often selected for fast convergence. This selection, however, results in an increased mean square error. The proposed detector uses the LMS algorithm with three different step size to obtain low mean square error and fast convergence. In this structure, errors which are obtained from each group are compared, and a minimum error is chosen to the selection block. In several step size LMS algorithms, filter coefficients for each group are upgraded using the output information of the selection block respectively. The advantages of this detector are that convergence time is fast, and that mean square error is low. However this detector has a defect that hardware complexity is increased.

  • A fully analytical recursive stochastic model to the normalized signed regressor LMS algorithm

    This work presents a new statistical analysis of the normalized signed regressor least mean square adaptive algorithm for Gaussian input signals. Deterministic recursive expressions are derived for the mean weight and mean square error behaviors, considering a large number of weights. The proposed approach does not require the use of numerical methods even for correlated inputs. An expression is derived for the steady-state misadjustment. Stability bounds are determined. Monte Carlo simulations show very good agreement between model and simulations during transient and steady-state even for large step sizes and small number of coefficients. The results emphasize the usefulness of this algorithm in applications for which the normalized least mean square algorithm (NLMS) is too complex.

  • An Improved Speech Denoising Algorithm Based on Adaptive Least Mean Square

    The excess mean squared errors is the major disadvantage in speech denoising algorithm based on least mean square, which increase linearly with the desired signal power. In order to improve the performance of the speech which exhibits in large power fluctuations, a new adaptive speech denoising algorithm based on adaptive least mean square is proposed, the improved speech denoising algorithm solve this question through minimizing the correlation between the error difference and input difference vector when the speech signal is powerful. According to the different noise environments, the proposed algorithm is simulated using different noise power levels. Simulation results show that the excess mean square error can improve about 20 dB in different noise environments based on the same complexity. It is benefit to the speech recognition process in communication system of voice.

  • Bayes Estimation of Reliability for Special k-out-of-m:G Systems

    Component lifetimes of a k-out-of-m: G system are s-independent and exponentially distributed. The Bayes-quadratic-loss estimator of reliability for the system is obtained using a conjugate (1-parameter case) or a noninformative (2-parameter case) prior when data are type-II censored. A simple approximation formula for the mean square error of the Bayes estimator is proposed. Based on the mean square-error criterion, the performance of the Bayes estimator under a noninformative prior is compared with that of the maximum likelihood and minimum variance s-unbiased estimators.



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