A frequency-domain method for generation of discrete-time analytic signals
We consider a common frequency-domain procedure hilbert for generating discrete-time analytic signals and show how it fails for a specific class of signals. A new frequency-domain technique ehilbert is formulated that solves the defect. Moreover, the new technique is applicable to all discrete-time...
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Veröffentlicht in: | IEEE transactions on signal processing 2006-09, Vol.54 (9), p.3343-3352 |
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description | We consider a common frequency-domain procedure hilbert for generating discrete-time analytic signals and show how it fails for a specific class of signals. A new frequency-domain technique ehilbert is formulated that solves the defect. Moreover, the new technique is applicable to all discrete-time real signals of even length. It is implemented by the introduction of one additional zero of the continuous spectrum of the analytic signal hilbert at a negative frequency. Both frequency-domain methods generate equal length discrete-time analytic signals. The new analytic signal preserves the original signal (real part) and also the zeros of the discrete spectrum hilbert in the negative frequencies. The greater attenuation at the negative frequencies affects the degree of aliasing of the analytic signal. It is measured by applying the analytic signal to an orthogonal wavelet transform and determining the improved transform shiftability |
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A new frequency-domain technique ehilbert is formulated that solves the defect. Moreover, the new technique is applicable to all discrete-time real signals of even length. It is implemented by the introduction of one additional zero of the continuous spectrum of the analytic signal hilbert at a negative frequency. Both frequency-domain methods generate equal length discrete-time analytic signals. The new analytic signal preserves the original signal (real part) and also the zeros of the discrete spectrum hilbert in the negative frequencies. The greater attenuation at the negative frequencies affects the degree of aliasing of the analytic signal. It is measured by applying the analytic signal to an orthogonal wavelet transform and determining the improved transform shiftability</description><subject>Aliasing</subject><subject>analytic signal</subject><subject>Applied sciences</subject><subject>Attenuation</subject><subject>Bandwidth</subject><subject>bandwidth compression</subject><subject>complex wavelet transform</subject><subject>Continuous wavelet transforms</subject><subject>Defects</subject><subject>Discrete Fourier transforms</subject><subject>Discrete wavelet transforms</subject><subject>Exact sciences and technology</subject><subject>Failure analysis</subject><subject>Frequency domain analysis</subject><subject>Hilbert transform</subject><subject>Information, signal and communications theory</subject><subject>Low pass filters</subject><subject>Mathematical analysis</subject><subject>Miscellaneous</subject><subject>Preserves</subject><subject>Signal analysis</subject><subject>Signal generators</subject><subject>Signal processing</subject><subject>Telecommunications and information theory</subject><subject>Transforms</subject><subject>Wavelet analysis</subject><subject>Wavelet transforms</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkM1LAzEQxRdRsFbPHrwsgnjadrIf-TgW8ZOCghW8hWx2UlO6m5psD_3vzdJCQRiYB_Obx-MlyTWBCSEgpovPj0kOQCeciQLyk2REREkyKBk9jRqqIqs4-z5PLkJYAZCyFHSUvM1S4_F3i53eZY1rle3SFvsf16TG-XSJHXrVW9elzqSNDdpjj1lvW0xVp9a73uo02GWU4TI5M3Hh1WGPk6-nx8XDSzZ_f359mM0zXVTQZ4iUx6krTQrdCGYIbxQSTmpdm1pAxXXdIOha5SXBhla10UJUudbQVKyGYpzc73033sXgoZdtzIXrterQbYPkgubARc4jefuPXLmtH7JKTikVRQEsQtM9pL0LwaORG29b5XeSgByalbFZOTQr983Gj7uDrQparY1Xnbbh-MahzDkbgt7sOYuIxzNlTAAp_gAHs4Jm</recordid><startdate>20060901</startdate><enddate>20060901</enddate><creator>Elfataoui, M.</creator><creator>Mirchandani, G.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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A new frequency-domain technique ehilbert is formulated that solves the defect. Moreover, the new technique is applicable to all discrete-time real signals of even length. It is implemented by the introduction of one additional zero of the continuous spectrum of the analytic signal hilbert at a negative frequency. Both frequency-domain methods generate equal length discrete-time analytic signals. The new analytic signal preserves the original signal (real part) and also the zeros of the discrete spectrum hilbert in the negative frequencies. The greater attenuation at the negative frequencies affects the degree of aliasing of the analytic signal. It is measured by applying the analytic signal to an orthogonal wavelet transform and determining the improved transform shiftability</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TSP.2006.879302</doi><tpages>10</tpages></addata></record> |
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subjects | Aliasing analytic signal Applied sciences Attenuation Bandwidth bandwidth compression complex wavelet transform Continuous wavelet transforms Defects Discrete Fourier transforms Discrete wavelet transforms Exact sciences and technology Failure analysis Frequency domain analysis Hilbert transform Information, signal and communications theory Low pass filters Mathematical analysis Miscellaneous Preserves Signal analysis Signal generators Signal processing Telecommunications and information theory Transforms Wavelet analysis Wavelet transforms |
title | A frequency-domain method for generation of discrete-time analytic signals |
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