IEEE Organizations related to Sensor Array And Multichannel Signal Processing

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Conferences related to Sensor Array And Multichannel Signal Processing

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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.


2020 IEEE International Solid- State Circuits Conference - (ISSCC)

ISSCC is the foremost global forum for solid-state circuits and systems-on-a-chip. The Conference offers 5 days of technical papers and educational events related to integrated circuits, including analog, digital, data converters, memory, RF, communications, imagers, medical and MEMS ICs.


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

For its 20th year edition, the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019, returns to the country that saw its birth, France. Held in Cannes, in the heart of the world renown “French Riviera” (Cote d’Azur in French), the SPAWC 2019 will exhibit a technical program complete with high profile plenaries, invited and contributed papers, all appearing under IEEE explore. A flagship workshop of the IEEE SP Society SPCOM technical committee, SPAWC 2019 will combine cutting edge research in the fields of signal processing, statistical learning, communication theory, wireless networking and more, together with an exciting social program on the glamorous and sunny Riviera.


2019 IEEE SENSORS

The IEEE Sensors Conference is a forum for presentation, discussion, and exchange of state-of-the art information including the latest research and development in sensors and their related fields. It brings together researchers, developers, and practitioners from diverse fields including international scientists and engineers from academia, research institutes, and companies to present and discuss the latest results in the general field of sensors.

  • 2018 IEEE SENSORS

    The IEEE Sensors Conference is a forum for presentation, discussion, and exchange of state -of-the art information including the latest research and development in sensors and their relatedfields. It brings together researchers, developers, and practitioners from diverse fields includinginternational scientists and engineers from academia, research institutes, and companies topresent and discuss the latest results in the general field of sensors.

  • 2017 IEEE SENSORS

    The IEEE Sensors Conference is a forum for presentation, discussion, and exchange of state -of-the art information including the latest research and development in sensors and their relatedfields. It brings together researchers, developers, and practitioners from diverse fields includinginternational scientists and engineers from academia, research institutes, and companies topresent and discuss the latest results in the general field of sensors.

  • 2016 IEEE Sensors

    The IEEE Sensors Conference is a forum for presentation, discussion, and exchange of state -of-the art information including the latest research and development in sensors and their related fields. It brings together researchers, developers, and practitioners from diverse fields including international scientists and engineers from academia, research institutes, and companies to present and discuss the latest results in the general field of sensors.

  • 2015 IEEE Sensors

    The IEEE Sensors Conference is a forum for presentation, discussion, and exchange of state -of-the art information including the latest research and development in sensors and their related fields. It brings together researchers, developers, and practitioners from diverse fieldsincluding international scientists and engineers from academia, research institutes, and companies topresent and discuss the latest results in the general field of sensors.

  • 2014 IEEE Sensors

    The IEEE Sensors Conference is a forum for presentation, discussion, andexchange of state -of-the art information including the latest research and development in sensors andtheir related fields. It brings together researchers, developers, and practitioners from diverse fieldsincluding international scientists and engineers from academia, research institutes, and companies topresent and discuss the latest results in the general field of sensors.

  • 2013 IEEE Sensors

    The IEEE SENSORS Conference is a forum for presentation, discussion, and exchange of state -of-the art information including the latest research and development in sensors and their related fields. It brings together researchers, developers, and practitioners from diverse fields including international scientists and engineers from academia, research institutes, and companies to present and discuss the latest results in the general field of sensors.

  • 2012 IEEE Sensors

    The IEEE Sensors Conference is a forum for presentation, discussion, and exchange of state-of-the art information including the latest research and development in sensors and their related fields. It brings together researchers, developers, and practitioners from diverse fields including international scientists and engineers from academia, research institutes, and companies to present and discuss the latest results in the general field of sensors.

  • 2011 IEEE Sensors

    The IEEE Sensors Conference is a forum for presentation, discussion, and exchange of state-of-the art information including the latest research and development in sensors and their related fields. It brings together researchers, developers, and practitioners from diverse fields including international scientists and engineers from academia, research institutes, and companies to present and discuss the latest results in the general field of sensors. IEEE SENSORS 2011 will include keynote addresses by eminen

  • 2010 IEEE Sensors

    The IEEE SENSORS 2010 Conference is a forum for state-of-the-art presentations on sensors and related topics covering from theory to application, device to system, modeling to implementation and from macro/nano to scale.

  • 2009 IEEE Sensors

    IEEE Sensors Conference 2009 is intended to provide a common forum for researchers, scientists, engineers and practitioners throughout the world to present their latest research findings, ideas, developments and applications in the area of sensors and sensing technology. IEEE Sensors Conference 2009 will include keynote addresses by eminent scientists as well as special, regular and poster sessions.

  • 2008 IEEE Sensors

    IEEE SENSORS 2008 solicits original and state-of-the-art contributions to sensors and related topics, covering from theory to application, from device to system, from modeling to implementation, and from macro to micro/nano in scale. Topics of interest include,but are not limitid to: Phenomena, Modeling, and Evaluation (Novel Sensing Principles, Theory and Modeling, Sensors Characterization, Evaluation and Testing, Data Handling and Mining) Chemical and Gas Sensors (Materials, Devices, Electronics N

  • 2007 IEEE Sensors

    IEEE SENSORS 2007 solicits original and state-of-the-art contributions to sensors and related topics, covering from theory to application, from device to system, from modeling to implementation, and from macro to micro/nano in scale.

  • 2006 IEEE Sensors

  • 2005 IEEE Sensors

  • 2004 IEEE Sensors

  • 2003 IEEE Sensors

  • 2002 IEEE Sensors


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Periodicals related to Sensor Array And Multichannel Signal Processing

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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; ...


Automation Science and Engineering, IEEE Transactions on

The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...


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.


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.


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Most published Xplore authors for Sensor Array And Multichannel Signal Processing

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Xplore Articles related to Sensor Array And Multichannel Signal Processing

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Generalized coprime array configurations

2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014

A coprime array consists of two uniform linear subarrays that construct an effective difference co-array with certain desirable characteristics. In this paper, we propose a generalized coprime array concept through the compression of the interelement spacing of one constituting subarray. As such, the existing variations of coprime array and nested array structures are represented as special cases. The achievable unique ...


Adaptive identification of nonlinear MIMO systems based on Volterra models with additive coupling

2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, 2010

Multiple-input multiple-output systems are increasingly important in a great number of fields, as is the case with telecommunications, robotics, biology, neuroscience, etc. In this paper, Volterra models are applied to a class of MIMO nonlinear systems, showing that linearity with respect to the coefficients ensures the availability of a global solution for the identification problem. The applicability of traditional learning ...


On the performance of a CFAR matched filter in the presence of signal mismatch

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016

We analytically evaluate the impact of a mismatch in the signal steering vector on the detection performance of a constant false alarm rate matched filter (CFAR-MF) in white Gaussian noise with unknown noise power. An infinite-sum expression for the detection probability of the CFAR-MF is derived in the mismatched case where the nominal signal steering vector is not aligned with ...


Estimation of the Regularization Parameter of an On-Line NMF with Minimum Volume Constraint

2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2018

In this paper, the estimation of the regularization parameter of the on-line Non-negative Matrix Factorization (NMF) with minimum volume constraint on sources is addressed. Adding a volume constraint in the model is important to ensure uniqueness of the solution and good data representation. However, the effectiveness of this approach is hampered by the optimal determination of the strength of minimum ...


Spectrum estimation from quantum-limited interferograms

Proceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop. SAM 2000 (Cat. No.00EX410), 2000

A quantitative model for interferogram data collected in a quantum-limited hyperspectral imaging system is derived. This model accounts for the geometry of the interferometer, the Poisson noise, and the parameterization of the mean of the noise in terms of the autocorrelation function of the incident optical signal. An estimation-theoretic approach to recovering the image spectrum is derived based on the ...


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Educational Resources on Sensor Array And Multichannel Signal Processing

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IEEE-USA E-Books

  • Generalized coprime array configurations

    A coprime array consists of two uniform linear subarrays that construct an effective difference co-array with certain desirable characteristics. In this paper, we propose a generalized coprime array concept through the compression of the interelement spacing of one constituting subarray. As such, the existing variations of coprime array and nested array structures are represented as special cases. The achievable unique lags as well as consecutive lags in the resulting virtual array are analytically expressed, and the direction-of-arrival estimation performance is examined using both the MUSIC algorithm and sparse signal reconstruction techniques.

  • Adaptive identification of nonlinear MIMO systems based on Volterra models with additive coupling

    Multiple-input multiple-output systems are increasingly important in a great number of fields, as is the case with telecommunications, robotics, biology, neuroscience, etc. In this paper, Volterra models are applied to a class of MIMO nonlinear systems, showing that linearity with respect to the coefficients ensures the availability of a global solution for the identification problem. The applicability of traditional learning algorithms, as Least-Mean-Square (LMS), is conditioned by eigenvalue spread, mainly dominated by nonlinear effects. This convergence issue and others are shown by means of a theoretical treatment and some examples.

  • On the performance of a CFAR matched filter in the presence of signal mismatch

    We analytically evaluate the impact of a mismatch in the signal steering vector on the detection performance of a constant false alarm rate matched filter (CFAR-MF) in white Gaussian noise with unknown noise power. An infinite-sum expression for the detection probability of the CFAR-MF is derived in the mismatched case where the nominal signal steering vector is not aligned with the actual one. This theoretical result is verified using Monte Carlo simulations.

  • Estimation of the Regularization Parameter of an On-Line NMF with Minimum Volume Constraint

    In this paper, the estimation of the regularization parameter of the on-line Non-negative Matrix Factorization (NMF) with minimum volume constraint on sources is addressed. Adding a volume constraint in the model is important to ensure uniqueness of the solution and good data representation. However, the effectiveness of this approach is hampered by the optimal determination of the strength of minimum volume term. To solve this problem, we formulate it as a bi-objective optimization problem and three Minimum Distance Criterion (MDC) strategies are proposed and evaluated. The three strategies yield similar results but one of them in particular yields an interesting tradeoff between accuracy and computation time.

  • Spectrum estimation from quantum-limited interferograms

    A quantitative model for interferogram data collected in a quantum-limited hyperspectral imaging system is derived. This model accounts for the geometry of the interferometer, the Poisson noise, and the parameterization of the mean of the noise in terms of the autocorrelation function of the incident optical signal. An estimation-theoretic approach to recovering the image spectrum is derived based on the likelihood function for the received data. The computations proposed constitute an alternating minimization algorithm.

  • Blind detection of exclusive source activity periods in reverberant acoustic environments

    Blind separation and dereverberation of acoustic sources is still considered a very challenging task despite many years of research and the availability of increasingly powerful computation engines. The complexity of the task can be significantly reduced for sources that exhibit sufficiently long <i>exclusive</i> <i>activity</i> <i>periods</i> (EAPs). EAPs are time intervals during which only one source is active and all other sources are inactive (i.e. zero). During EAPs the estimation of the underlying system parameters simplifies from a MIMO type to a SIMO type. The existence of EAPs is not guaranteed for arbitrary signal classes. EAPs occur very frequently, however, in recordings of conversational speech. In this paper we propose a new low complexity method for EAP detection which significantly outperforms earlier approaches.

  • Comparison of the CAF-DF and SAGE algorithms in multipath channel parameter estimation

    In this paper, performance of the recently proposed cross ambiguity function - direction finding (CAF-DF) technique is compared with the space alternating generalized expectation maximization (SAGE) technique. The CAF-DF, iteratively estimates direction of arrival (DOA), time-delay, Doppler shift and amplitude corresponding to each impinging signal onto an antenna array by utilizing the cross ambiguity function. On synthetic signals, based on Monte Carlo trials, performances of the algorithms are tested in terms of root mean squared error (rMSE) at different signal-to-noise ratios (SNR). Cramer-Rao lower bound is included for statistical comparisons. Simulation results indicate the superior performance of the CAF-DF technique over SAGE technique for low and medium SNR values.

  • 2-D sensor position perturbation analysis: equivalence to AWGN on array outputs

    The performance of a subspace beamformer, namely the multiple signal classification algorithm (MUSIC), is scrutinized in the presence of sensor position errors. Based on a perturbation model, a relationship between the array autocorrelation matrix and the source autocorrelation matrix is established. It is shown that under certain assumptions on the source signals, the Gaussian sensor perturbation errors can be modelled as additive white Gaussian noise (AWGN) for an array where sensor positions are known perfectly. This correspondence can be used to equate position errors to an equivalent signal-to-noise ratio (SNR) for AWGN in performance evaluation. Finally, Cramer-Rao bound for the position perturbations that can be computed using the Cramer-Rao bound relations for the additive Gaussian noise case at high SNR's.

  • Optimal power allocation in opportunistic relaying with outdated CSI

    In this paper, we study the impact of outdated channel state information (CSI) on a cooperative system based on opportunistic relay selection (ORS). The study is carried out by obtaining an analytical expression for the outage probability, defined as the probability that the instantaneous mutual information is lower than a target rate. Besides, we propose the optimal power allocation aimed at minimizing the outage probability when the available CSI is subject to impairments. As shown in the paper, the proposed strategy provides significant gains when compared with uniform power allocation.

  • Sparsity aware nonlinear multichannel ultrasonic tomographic imaging

    This paper presents an accelerate projected steepest descent method for nonlinear ultrasonic tomographic imaging with sparsity constraints in a multiple-input multiple-output configuration. The proposed method introduces the emerging MIMO signal processing techniques and sparsity constrained image reconstruction methods to the traditional computational imaging field, thus significantly improves the speed of image formation compared with conventional imaging method while achieving high quality images. Using numerical examples, we demonstrate the success of the proposed algorithm.



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