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Kutyniok, Gitta.

Overview

Works:	2 works in 3 publications in 1 languages

Titles

Compressed Sensing and Its Applications = Third International MATHEON Conference 2017 / by: Mathar, Rudolf.; Calderbank, Robert.; Kutyniok, Gitta.; SpringerLink (Online service); Boche, Holger.; Petersen, Philipp.; Caire, Giuseppe. (Language materials, printed) , [http://id.loc.gov/vocabulary/relators/edt]

Shearlets = multiscale analysis for multivariate data / by: Kutyniok, Gitta.; Labate, Demetrio.; SpringerLink (Online service) (Language materials, printed)

Mathematical aspects of deep learning by: Kutyniok, Gitta.; Grohs, Philipp. (Language materials, printed)

Compressed Sensing and its Applications = MATHEON Workshop 2013 / by: Vybíral, Jan.; Boche, Holger.; SpringerLink (Online service); Calderbank, Robert.; Kutyniok, Gitta. (Language materials, printed) , [http://id.loc.gov/vocabulary/relators/edt]

Compressed sensing : = theory and applications / by: Eldar, Yonina C.; Kutyniok, Gitta. (Language materials, printed)

Compressed Sensing in Information Processing by: SpringerLink (Online service); Kutyniok, Gitta.; Kunsch, Robert J.; Rauhut, Holger. (Language materials, printed) , [http://id.loc.gov/vocabulary/relators/edt]

Finite frames = theory and applications / by: Kutyniok, Gitta.; Casazza, Peter G.; SpringerLink (Online service) (Language materials, printed)

Subjects

Computer mathematics. Computer science—Mathematics. Numerical analysis. Fourier Analysis. Digital and Analog Signal Processing. Signal processing. Machine learning. Wavelets (Mathematics) Data Storage Representation. Frames (Vector analysis) Harmonic analysis. Abstract Harmonic Analysis. Speech processing systems. Computational Mathematics and Numerical Analysis. Multivariate analysis. Mathematics. Coding theory. Matrix theory. Deep learning (Machine learning) Operator Theory. Image processing. Algebra. Signal, Image and Speech Processing. Information theory. Coding and Information Theory. Linear and Multilinear Algebras, Matrix Theory. Numerical Analysis. Applications of Mathematics. Approximations and Expansions. Image Processing. Information and Communication, Circuits. Mathematical Applications in Computer Science. Machine Learning. Fourier analysis. Computational Science and Engineering. Mathematics—Data processing. Computer Imaging, Vision, Pattern Recognition and Graphics.