Distribution & Interpolation Spaces

Related lectures (30)

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Explores the Fourier transformation, Parseval relation, weak convergence, and generalized transformations in signals and systems.

Covers the concepts of compression and prediction using prefix-free codes and distributions.

Explores compact subsets of R^n, convergence theorems, and set properties.

Explores linear operations, convergence, sequences, and compact sets in mathematical analysis.

Introduces probability theory, random variables, and distributions, with a focus on their applications in atomic diffusion.

Explores the benefits of deeper networks in deep learning and the importance of over-parameterization and generalization.

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Covers the concept of compression and constructing prefix-free codes based on given information.

Explores Dirichlet series convergence properties and absolute convergence conditions, with examples and applications.

Covers the joint equidistribution of CM points and the ergodic decomposition theorem in compact abelian groups.