Linear Algebra: Basics and Applications

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Related lectures (28)

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Linear Algebra: Applications and Algorithms

Explores linear algebra's applications and algorithms in various fields, offering theoretical foundations and practical problem-solving strategies.

Fourier Transform: Concepts and Applications

Covers the Fourier transform, its properties, applications in signal processing, and differential equations, emphasizing the concept of derivatives becoming multiplications in the frequency domain.

Linear Algebra: Projection and Rotation

Covers projection, rotation, white Gaussian noise, and waveform observation in linear algebra.

Decomposition LLT: Example

Explains the decomposition LL² with an example and detailed calculations.

Signal Representation

Discusses signal representation, focusing on mathematical expressions and inequalities in signal processing.

Matrix-Matrix Multiplication: Algorithms and Applications

Explores theoretical and practical aspects of fast matrix-matrix multiplication algorithms and their significance in computer science.

Neural Signals and Signal Processing

Explores nuclear magnetic resonance, MRI principles, pulse sequences, image reconstruction, safety considerations, and volume normalization in brain imaging.

Solving Parity Games in Practice

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

LabVIEW Programming Essentials

Explores LabVIEW essentials, troubleshooting common issues, managing cache, and data visualization techniques.

Linear Algebra: Matrix Transformations and Determinants

Explores matrix transformations, coordinates calculation, and determinant properties in linear algebra.