Lectures related to Linear Algebra: Basics and Applications

Explores discrete signals, linear systems, categorization examples, and convolution properties in signal processing.

Explores fundamental notions in image and video processing, covering applications and key concepts like color quantization and 2D Fourier Transform properties.

Neural Signals and Signal Processing

Covers neural signals, brain enthusiasm, neuroimaging, and statistical analysis in neuroimaging studies.

Linear Algebra in 3D: Determinants and Inverses

Explores determinants in 3D space and their role in linear algebra.

Digital Signal Processing: Transform in Z

Explores the Transform in Z, a key tool in digital signal processing.

Eigenvalues and Optimization: Numerical Analysis Techniques

Discusses eigenvalues, their calculation methods, and their applications in optimization and numerical analysis.

Matrix Norms: Spectral and Frobenius

Covers matrix norms, including the spectral and Frobenius norms.

Introduction to Optimization

Introduces linear algebra, calculus, and optimization basics in Euclidean spaces, emphasizing the power of optimization as a modeling tool.