Efficient Implementation of Iterative Adaptive Approach Spectral Estimation Techniques
This paper presents computationally efficient implementations for several recent algorithms based on the iterative adaptive approach (IAA) for uniformly sampled one- and two-dimensional data sets, considering both the complete data case, and the cases when the data sets are missing samples, either l...
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| Veröffentlicht in: | IEEE transactions on signal processing 2011-09, Vol.59 (9), p.4154-4167 |
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| container_title | IEEE transactions on signal processing |
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| creator | Glentis, George-Othon Jakobsson, A. |
| description | This paper presents computationally efficient implementations for several recent algorithms based on the iterative adaptive approach (IAA) for uniformly sampled one- and two-dimensional data sets, considering both the complete data case, and the cases when the data sets are missing samples, either lacking arbitrary locations, or having gaps or periodically reoccurring gaps. By exploiting the method's inherent low displacement rank, together with the development of suitable Gohberg-Semencul representations, and the use of data dependent trigonometric polynomials, the proposed implementations are shown to offer a reduction of the necessary computational complexity by at least one order of magnitude. Numerical simulations together with theoretical complexity measures illustrate the achieved performance gain. |
| doi_str_mv | 10.1109/TSP.2011.2145376 |
| format | Article |
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By exploiting the method's inherent low displacement rank, together with the development of suitable Gohberg-Semencul representations, and the use of data dependent trigonometric polynomials, the proposed implementations are shown to offer a reduction of the necessary computational complexity by at least one order of magnitude. Numerical simulations together with theoretical complexity measures illustrate the achieved performance gain.</description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/TSP.2011.2145376</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Applied sciences ; Complexity ; Computational complexity ; Computational efficiency ; Convergence ; Covariance matrix ; Detection, estimation, filtering, equalization, prediction ; Discrete Fourier transforms ; Estimation ; Exact sciences and technology ; fast algorithms ; Gain ; Gaps ; Information, signal and communications theory ; iterative adaptive approach (IAA) ; Iterative methods ; Matematik ; Mathematical models ; Mathematics ; Natural Sciences ; Naturvetenskap ; Polynomials ; Probability Theory and Statistics ; Sannolikhetsteori och statistik ; Signal and communications theory ; Signal representation. 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By exploiting the method's inherent low displacement rank, together with the development of suitable Gohberg-Semencul representations, and the use of data dependent trigonometric polynomials, the proposed implementations are shown to offer a reduction of the necessary computational complexity by at least one order of magnitude. Numerical simulations together with theoretical complexity measures illustrate the achieved performance gain.</description><subject>Applied sciences</subject><subject>Complexity</subject><subject>Computational complexity</subject><subject>Computational efficiency</subject><subject>Convergence</subject><subject>Covariance matrix</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Discrete Fourier transforms</subject><subject>Estimation</subject><subject>Exact sciences and technology</subject><subject>fast algorithms</subject><subject>Gain</subject><subject>Gaps</subject><subject>Information, signal and communications theory</subject><subject>iterative adaptive approach (IAA)</subject><subject>Iterative methods</subject><subject>Matematik</subject><subject>Mathematical models</subject><subject>Mathematics</subject><subject>Natural Sciences</subject><subject>Naturvetenskap</subject><subject>Polynomials</subject><subject>Probability Theory and Statistics</subject><subject>Sannolikhetsteori och statistik</subject><subject>Signal and communications theory</subject><subject>Signal representation. Spectral analysis</subject><subject>Signal, noise</subject><subject>Spectra</subject><subject>spectrum estimation theory and methods</subject><subject>Telecommunications and information theory</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdUU2LFDEUDKLgOnoXvDSC4KXHvHz3cVlGHRhQ2FG8hXT6hc3S090m3Sv-ezP0MAcPj9QjVcUripC3QLcAtPl0vP--ZRRgy0BIrtUzcgONgJoKrZ4XTCWvpdG_XpJXOT9SCkI06ob83IUQfcRhrvanqcdTQW6O41CNodrPmMryhNVt56YVTFManX-o7if0c3J9tctzPK2SI_qHIf5eML8mL4LrM765vBvy4_PuePe1Pnz7sr-7PdReMDbXHXSdDgqV0B5lCKo1TDkm0RknOsUFAEhJuWe-9WDQYSuZZpIq1aJAzjfksPrmPzgtrZ1SuSX9taOLtl-mMm0Zm9GahrW-a8EilY0VBo01WoOlKASlGqjTbbH7uNqVkOcYsz3F7LHv3YDjki0oDVxrwaBQ3_9HfRyXNJSw1hhGqWGNKSS6knwac04YrgcCtefabKnNnmuzl9qK5MPF12Xv-pDc4GO-6piQDZOFuiHvVl5ExOu31JI3kvF_m5agAw</recordid><startdate>20110901</startdate><enddate>20110901</enddate><creator>Glentis, George-Othon</creator><creator>Jakobsson, A.</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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| subjects | Applied sciences Complexity Computational complexity Computational efficiency Convergence Covariance matrix Detection, estimation, filtering, equalization, prediction Discrete Fourier transforms Estimation Exact sciences and technology fast algorithms Gain Gaps Information, signal and communications theory iterative adaptive approach (IAA) Iterative methods Matematik Mathematical models Mathematics Natural Sciences Naturvetenskap Polynomials Probability Theory and Statistics Sannolikhetsteori och statistik Signal and communications theory Signal representation. Spectral analysis Signal, noise Spectra spectrum estimation theory and methods Telecommunications and information theory |
| title | Efficient Implementation of Iterative Adaptive Approach Spectral Estimation Techniques |
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