Signals & Systems I: Fourier Transformation and Distributions

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Covers probability theory, distributions, and estimation in statistics, emphasizing accuracy, precision, and resolution of measurements.

Introduces the basics of probability models, covering random variables, distributions, and statistical estimation.

Introduces probability, estimation methods, linear models, testing, and advanced regression techniques.

Covers the laws of transformation of speeds and accelerations, including the rotation of points and dynamic movement principles.

Covers the properties of the integral on S-up, including linearity and monotony.

Covers the exponential family of distributions and the Ising model, explaining magnetism through dipoles and spins.

Covers the fundamental solutions of the Laplace equation and introduces distributions.

Explores geometric transformations like translation and homothety in the plane.

Explores distributions, linear systems, impulse response, convolution operators, and causal systems in signals and systems.

Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.