000			01959nam a2200241Ia 4500
005			20250409101426.0
008			230421s2013||||xx |||||||||||||| ||eng||
020			_a9781493900633
041			_aEnglish
082			_a621.3822 F68, 1
100			_aFoucart, Simon _eAuthor
100			_aRauhut, Holger _eCo-Author _92324
245		2	_aA mathematical introduction to compressive sensing
250			_a1st ed.
260			_aNew York: _bSpringer, _c2013.
300			_axviii, 625p.; 21cms.
490			_aApplied and Numerical Harmonic Analysis
500			_aAt the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on 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			_aApplied physics _xCompressive Sensing (Mathematical) _92477
650			_aCompressive sensing and signal processing _96106
650			_xSignal processing--Mathematics _92478
942			_cBK
999			_c823 _d823