000			a
999			_c33056 _d33056
008			240319b xxu||||| |||| 00| 0 eng d
020			_a9783319595320
082			_a621.3822 _bGEI
100			_aGeiger, Bernhard C.
245			_aInformation Loss in Deterministic Signal Processing Systems
260			_bSpringer, _c2018 _aCham :
300			_axiv, 145 p. ; _bill., (some col.), _c25 cm
365			_b99.99 _c€ _d93.50
490			_aUnderstanding Complex Systems, _v1860-0832
504			_aIncludes bibliographical references.
520			_aThis book introduces readers to essential tools for the measurement and analysis of information loss in signal processing systems. Employing a new information-theoretic systems theory, the book analyzes various systems in the signal processing engineer{u2019}s toolbox: polynomials, quantizers, rectifiers, linear filters with and without quantization effects, principal components analysis, multirate systems, etc. The user benefit of signal processing is further highlighted with the concept of relevant information loss. Signal or data processing operates on the physical representation of information so that users can easily access and extract that information. However, a fundamental theorem in information theory{u2014}data processing inequality{u2014}states that deterministic processing always involves information loss. These measures form the basis of a new information-theoretic systems theory, which complements the currently prevailing approaches based on second-order statistics, such as the mean-squared error or error energy. This theory not only provides a deeper understanding but also extends the design space for the applied engineer with a wide range of methods rooted in information theory, adding to existing methods based on energy or quadratic representations. Collapse
650			_aCybernetics and systems theory
650			_aImaging systems and technology
650			_aScience Physics
650			_aSignal processing
650			_aDigital techniques
650			_aMathematics
650			_aStatistical physics
650			_aEngineering Electronics
700			_aKubin, Gernot
942			_2ddc _cBK