Conferences related to Chebyshev approximation

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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 IEEE 70th Electronic Components and Technology Conference (ECTC)

ECTC is the premier international conference sponsored by the IEEE Components, Packaging and Manufacturing Society. ECTC paper comprise a wide spectrum of topics, including 3D packaging, electronic components, materials, assembly, interconnections, device and system packaging, optoelectronics, reliability, and simulation.


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

The Conference focuses on all aspects of instrumentation and measurement science andtechnology research development and applications. The list of program topics includes but isnot limited to: Measurement Science & Education, Measurement Systems, Measurement DataAcquisition, Measurements of Physical Quantities, and Measurement Applications.


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Periodicals related to Chebyshev approximation

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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.


Antennas and Wireless Propagation Letters, IEEE

IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.


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


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 ...


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Most published Xplore authors for Chebyshev approximation

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Xplore Articles related to Chebyshev approximation

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Linear Array Pattern Synthesis

Phased Array Antennas, None

This chapter contains sections titled:IntroductionDolph–Chebyshev ArraysTaylor One‐Parameter DistributionTaylor_N_‐Bar Aperture DistributionLow‐Sidelobe DistributionsVilleneuve_N_‐Bar Array DistributionDifference PatternsSidelobe Envelope ShapingShaped Beam SynthesisThinned ArraysAcknowledgmentReferences


Chebyshev design of FIR filters with arbitrary magnitude and phase responses

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

This paper presents a method for the design of nonlinear phase FIR digital filters with complex or real-valued coefficients using the Chebyshev error criterion. Three different problems are considered: Complex Chebyshev approximation with additional weighting of the resulting magnitude and phase errors, simultaneous Chebyshev approximation of a given magnitude and phase response, and simultaneous Chebyshev approximation of a given magnitude ...


Superdirective Arrays

Phased Array Antennas, None

This chapter contains sections titled:Historical NotesMaximum Array DirectivityConstrained OptimizationMatching of Superdirective ArraysReferences


Conformal Arrays

Phased Array Antennas, None

This chapter contains sections titled:ScopeRing ArraysArrays on CylindersSector Arrays on CylindersArrays on Cones and SpheresAcknowledgmentsReferences


Sparse Coefficient FIR Filter Design

IEEE 1992 International Conference on Consumer Electronics Digest of Technical Papers, 1992

None


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Educational Resources on Chebyshev approximation

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IEEE-USA E-Books

  • Linear Array Pattern Synthesis

    This chapter contains sections titled:IntroductionDolph–Chebyshev ArraysTaylor One‐Parameter DistributionTaylor_N_‐Bar Aperture DistributionLow‐Sidelobe DistributionsVilleneuve_N_‐Bar Array DistributionDifference PatternsSidelobe Envelope ShapingShaped Beam SynthesisThinned ArraysAcknowledgmentReferences

  • Chebyshev design of FIR filters with arbitrary magnitude and phase responses

    This paper presents a method for the design of nonlinear phase FIR digital filters with complex or real-valued coefficients using the Chebyshev error criterion. Three different problems are considered: Complex Chebyshev approximation with additional weighting of the resulting magnitude and phase errors, simultaneous Chebyshev approximation of a given magnitude and phase response, and simultaneous Chebyshev approximation of a given magnitude and group delay response. A linearization approach leads to a problem formulation that allows the use of stable algorithms with guaranteed convergence. It is shown that for this linear approach the simultaneous Chebyshev approximation of a desired magnitude and phase response is a special case of complex Chebyshev approximation with independent weighting of the magnitude and phase errors. Two existing design methods are included in this method as special cases.

  • Superdirective Arrays

    This chapter contains sections titled:Historical NotesMaximum Array DirectivityConstrained OptimizationMatching of Superdirective ArraysReferences

  • Conformal Arrays

    This chapter contains sections titled:ScopeRing ArraysArrays on CylindersSector Arrays on CylindersArrays on Cones and SpheresAcknowledgmentsReferences

  • Sparse Coefficient FIR Filter Design

    None

  • Bessel planar arrays

    In this paper, we introduce a new class of planar arrays that we call the Bessel planar arrays. A formula for the current distribution in the elements of these arrays is presented, which is related to Bessel functions. For the Bessel planar arrays, the maximal sidelobe level is controllable, the directivity is very high, and the half-power beam width is slightly larger compared to the optimal Chebyshev planar arrays. Methods to set the maximal sidelobe level and compute the directivity and the half-power beam width are described, and numerical examples are given to illustrate the features of the proposed arrays.

  • A new scheme for designing IIR filters with finite wordlength coefficients

    A scheme for designing IIR digital filters, with specified coefficient wordlengths based on successive digitization and reoptimization, is presented and compared to related approaches via a number of design examples. The ordered digitization of the coefficients based on their sensitivity, with each digitization followed by reoptimization of the remaining coefficients, results in a much reduced computation effort in comparison to related design approaches.

  • Fast multiplierless recursive transforms using Ramanujan numbers

    A special class of multiplierless transforms for computing discrete cosine transform (DCT) is introduced. This algorithm is completely multiplierless to compute an N-point DCT using Ramanujan Number of order -1 and order-2. The algorithm requires evaluation of Cosine angles which are multiples of 2pi/N. If the transform size N is a Ramanujan Number and if 2pi/N cong 2<sup>-a</sup>, then the cosine functions can be computed by shifts and adds employing Chebyshev type of recursion. In this paper, an analytical extension of the algorithm is made for 2-D Ramanujan DCT for image coding applications.

  • New TE01 Waveguide Bends

    Two new TE<sub>01</sub> waveguide bends are suggested. The first version is resulted by the synthesis procedure which generates an optimal profile of the bending curvature. The second version is based on an eigen mode propagating in elliptic cross-section waveguide. The curvature profile is optimized by means of the theory of Chebyshev's transducers.

  • Design of chaotic spread-spectrum sequences with good correlation properties for DS/CDMA

    According to the advantages of chaotic analog sequences and chaotic binary sequences, this paper proposes a method of generating chaotic binary spread- spectrum sequences by multilevel quantifying. The performance of DS/CDMA communication system is closely related to the mean-square cross-correlation value between sequences, so the distribution of the correlation and the mean- square correlation between the sequences is presented. The theoretical analysis and the results of simulation show that the spread-spectrum sequences generated by the method have good correlation properties, and their quantity is very large.



Standards related to Chebyshev approximation

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Jobs related to Chebyshev approximation

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