Conferences related to IEEE Transactions on Signal Processing

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Periodicals related to IEEE Transactions on Signal Processing

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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.


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 Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


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 IEEE Transactions on Signal Processing

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Xplore Articles related to IEEE Transactions on Signal Processing

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Canonical Correlation Analysis for Data Fusion and Group Inferences

IEEE Signal Processing Magazine, 2010

We have presented two CCA-based approaches for data fusion and group analysis of biomedical imaging data and demonstrated their utility on fMRI, sMRI, and EEG data. The results show that CCA and M-CCA are powerful tools that naturally allow the analysis of multiple data sets. The data fusion and group analysis methods presented are completely data driven, and use simple ...


Reply to “Comments on ‘A Recursive Least M-Estimate Algorithm for Robust Adaptive Filtering in Impulsive Noise: Fast Algorithm and Convergence Performance Analysis’”

IEEE Transactions on Signal Processing, 2009

We appreciate the comments by Bershad [ldquoComments on `A Recursive Least M-Estimate Algorithm for Robust Adaptive Filtering in Impulsive Noise: Fast Algorithm and Convergence Performance Analysis,'rdquo IEEE Transactions on Signal Processing, vol. 57, no. 1, January 2009] on an assumption of our paper [ldquoA Recursive Least M-Estimate Algorithm for Robust Adaptive Filtering in Impulsive Noise: Fast Algorithm and Convergence Performance ...


Reply to “Comments on `A Blind Signal Separation Method for Multiuser Communications'”

IEEE Transactions on Signal Processing, 2007

In this correspondence, we reply to the comments in Gu ["Comments on `A blind signal separation method for multiuser communications'", IEEE Transactions on Signal Processing, vol. 55, no. 5, pp. 2355-2356, May 2007]. We explain that the global convergence analysis of the method in Castedo ["A blind signal separation method for multiuser communications", IEEE Transactions on Signal Processing, vol. 45, ...


Comments on “Waveform Design for Radar STAP in Signal Dependent Interference”

IEEE Transactions on Signal Processing, 2018

We read with great interest the recently published paper [1] (together with some additional technical details in [2]) dealing with an important topic for the radar signal processing Community.With regret, we noticed that the mentioned reference [1] provides some claims which do not agree with what we proved in paper [3]; contains some technical inconsistencies from the optimization theory point ...


Correction to “Extended array manifolds: functions of array manifolds” [Jul 11 3272-3287]

IEEE Transactions on Signal Processing, 2011

The author presents revisions to various equations and formulas from the above-named article.


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Educational Resources on IEEE Transactions on Signal Processing

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IEEE-USA E-Books

  • Canonical Correlation Analysis for Data Fusion and Group Inferences

    We have presented two CCA-based approaches for data fusion and group analysis of biomedical imaging data and demonstrated their utility on fMRI, sMRI, and EEG data. The results show that CCA and M-CCA are powerful tools that naturally allow the analysis of multiple data sets. The data fusion and group analysis methods presented are completely data driven, and use simple linear mixing models to decompose the data into their latent components. Since CCA and M-CCA are based on second-order statistics they provide a relatively lessstrained solution as compared to methods based on higherorder statistics such as ICA. While this can be advantageous, the flexibility also tends to lead to solutions that are less sparse than those obtained using assumptions of non-Gaussianity-in particular superGaussianity-at times making the results more difficult to interpret. Thus, it is important to note that both approaches provide complementary perspectives, and hence it is beneficial to study the data using different analysis techniques.

  • Reply to “Comments on ‘A Recursive Least M-Estimate Algorithm for Robust Adaptive Filtering in Impulsive Noise: Fast Algorithm and Convergence Performance Analysis’”

    We appreciate the comments by Bershad [ldquoComments on `A Recursive Least M-Estimate Algorithm for Robust Adaptive Filtering in Impulsive Noise: Fast Algorithm and Convergence Performance Analysis,'rdquo IEEE Transactions on Signal Processing, vol. 57, no. 1, January 2009] on an assumption of our paper [ldquoA Recursive Least M-Estimate Algorithm for Robust Adaptive Filtering in Impulsive Noise: Fast Algorithm and Convergence Performance Analysis,rdquo IEEE Transactions on Signal Processing, vol. 52, no. 4, April 2004]. In this reply, we elaborate further on this assumption, which was originally introduced as an approximation to simplify the performance analysis. Modifications and references to a related extension of Price's theorem for independent mixtures are outlined. We wish this will clarify the issues raised.

  • Reply to “Comments on `A Blind Signal Separation Method for Multiuser Communications'”

    In this correspondence, we reply to the comments in Gu ["Comments on `A blind signal separation method for multiuser communications'", IEEE Transactions on Signal Processing, vol. 55, no. 5, pp. 2355-2356, May 2007]. We explain that the global convergence analysis of the method in Castedo ["A blind signal separation method for multiuser communications", IEEE Transactions on Signal Processing, vol. 45, no. 5, pp. 1343-1348, May 1997] can be completed as an extension of the results that were already presented. Also, we recall that two of the authors put forward (Dapena and Castedo ["Stochastic gradient adaptive algorithms for blind source separation", Elsevier Signal Processing, vol. 75, pp. 11-27]) a similar method with more attractive properties whose convergence analysis is not affected by the counterexample provided in Gu et al

  • Comments on “Waveform Design for Radar STAP in Signal Dependent Interference”

    We read with great interest the recently published paper [1] (together with some additional technical details in [2]) dealing with an important topic for the radar signal processing Community.With regret, we noticed that the mentioned reference [1] provides some claims which do not agree with what we proved in paper [3]; contains some technical inconsistencies from the optimization theory point of view. Thus, respectfully, we feel obliged to provide the necessary clarifications and corrections. Specifically, this "comments on" paper has the following technical purposes: a) to rectify some untrue claims by the Authors of [1] about reference [3]; b) to show that the optimization problem arising in [1] (eq. (17)) is a special instance of the more general optimization problem addressed in [3] (eq. (13)); c) to prove that the solution of the waveform design problem in [1] (eq. (25)) given by eq. (36) is not generally correct. [1] P. Setlur and M. Rangaswamy, "Waveform Design for Radar STAP in Signal Dependent Interference," IEEE Transactions on Signal Processing, vol. 64, no. 1, pp. 19-34, Jan. 2016. [2] P. Setlur and M. Rangaswamy, Joint Filter and Waveform Design for Radar STAP in Signal Dependent Interference, Tech. Rep. DTIC, available at : https: // arxiv.org/abs/ 1510. 00055, US Air Force Res. Lab., Sensors Directorate, WPAFB, Dayton, OH, 2014. [3] A. Aubry, A. De Maio, A. Farina, and M. Wicks, "Knowledge-Aided (Potentially Cognitive) Transmit Signal and Receive Filter Design in Signal-Dependent Clutter," IEEE Transactions on Aerospace and Electronic Systems, vol. 49, no. 1, pp. 93-117, Jan. 2013.

  • Correction to “Extended array manifolds: functions of array manifolds” [Jul 11 3272-3287]

    The author presents revisions to various equations and formulas from the above-named article.

  • Correction to "Noise amplification of periodic nonuniform sampling"

    None

  • Erratum to “Nested Arrays: A Novel Approach to Array Processing With Enhanced Degrees of Freedom” [Aug 10 4167-4181]

    In the above titled paper (ibid., vol. 58, no. 8, pp. 4167-4181, Aug. 10), the second unnumbered equation in the left column was incorrect. The correct version is presented here.

  • Reply to "Comments on 'A variationl approach to the extraction of in-phase and quadrature components'"

    None

  • Correction to "Occam Filters For Stochastic Sources With Application To Digital Images"

    None

  • 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.



Standards related to IEEE Transactions on Signal Processing

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(Replaced) IEEE Standard VHDL Language Reference Manual

his standard revises and enhances the VHDL language reference manual (LRM) by including a standard C language interface specification; specifications from previously separate, but related, standards IEEE Std 1164 -1993,1 IEEE Std 1076.2 -1996, and IEEE Std 1076.3-1997; and general language enhancements in the areas of design and verification of electronic systems.



Jobs related to IEEE Transactions on Signal Processing

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