000 | 01901nam a2200265Ia 4500 | ||
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005 | 20250409101054.0 | ||
008 | 230421s2013||||xx |||||||||||||| ||eng|| | ||
020 | _a9781493900633 | ||
041 | _aEnglish | ||
082 | _a621.3822 F66, 1 | ||
100 |
_aFoucart, Simon _eAuthor |
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100 |
_aRauhut, Holger _eCo-Author _92324 |
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245 | 2 | _aA mathematical introduction to compressive sensing | |
250 | _a1st ed. | ||
260 |
_aNew York: _bBirkhauser, _c2013. |
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300 | _axviii, 625p.; 21cms. | ||
490 | _aApplied and Numerical Harmonic Analysis | ||
500 | _aon the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domains. In the areas of applied mathematics, electrical engineering, and theoretical computer science, an explosion of research activity has already followed the theoretical results that highlighted the efficiency of the basic principles. The elegant ideas behind these principles are also of independent interest to pure mathematicians. A Mathematical Introduction to Compressive Sensing gives a detailed account of the core theory upon which the field is build. With only moderate prerequisites, it is an excellent textbook for graduate courses in mathematics, engineering, and computer science. It also serves as a reliable resource for practitioners and researchers in these disciplines who want to acquire a careful understanding of the subject. A Mathematical Introduction to Compressive Sensing uses a mathematical perspective to present the core of the theory underlying compressive sensing. | ||
650 |
_aSignal processing _xDigital techniques _xMathematics _92320 |
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650 |
_aComputer science _947 |
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650 |
_aTelecommunication _92321 |
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650 |
_aCompressed sensing (Telecommunication) _92322 |
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650 |
_aFunctional analysis _92323 |
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942 | _cBK | ||
999 |
_c821 _d821 |