Lectures related to Sine and cosine transforms

Explores Fourier series coefficients, periodicity, and series relations.

Explores trigonometric polynomials, emphasizing Fourier inversion and Plancherel formulas.

Covers the Fourier inversion formula, exploring its mathematical concepts and applications, emphasizing the importance of understanding the sign.

Covers the properties of transforms and their applications in mathematics.

Explores eigenfaces, DFT, DCT, and wavelet transforms in image processing.

Covers determinantal point processes, sine-process, and their extrapolation in different spaces.

Explores the intuition behind transforms of the place and addresses audience questions on integral calculations and function choices.

Covers the definition and properties of convolution of two functions and explores radioactive material decay rates.

Covers the Fourier inversion formula and the Plancherel identity, emphasizing their importance in mathematical analysis.

Covers Fourier series, periodic functions, and Fourier transforms.

Explores shallow water waves, stability conditions, and tsunamis through simulations and analytical solutions.

Covers the solutions to the midterm exam, focusing on multiple choice questions and detailed derivations.

Covers EM fields of moving charged particles and Green functions.

Explores wave patterns, Fourier transforms, group velocity, and Gaussian spectra in hydrodynamics.

Covers the analysis of LTI communication systems and reconstruction techniques for band-limited signals.

Explores Fourier transforms, including properties, convolution, Parseval's theorem, and energy spectral density for non-periodic functions.

Explores the Schrödinger equation in quantum mechanics, emphasizing conservation of probability and numerical schemes.

Explores Fourier series for periodic functions, emphasizing coefficient calculation and function representation using sine and cosine terms.

Covers the concept of Fourier series and their practical applications in signal processing.

Explores the solution of the 1D Schrödinger equation using Fourier transforms and convolution techniques.