Convolutional Coder Introduction

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Convolutional Codes: Encoding and Decoding

Explains the encoding and decoding process of convolutional codes using constellation prints.

Neural Signals and Signal Processing

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

Neural Signals and Signal Processing: Hemodynamic Imaging

Explores hemodynamic imaging techniques to measure brain activity and understand brain structure and function.

Neural Signals and Signal Processing

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

Convolutional Codes: Analysis and Applications

Delves into the analysis and applications of convolutional codes, highlighting the significance of correct implementation for optimal results.

Information Theory: Source Coding, Cryptography, Channel Coding

Covers source coding, cryptography, and channel coding in communication systems, exploring entropy, codes, error channels, and future related courses.

Stochastic Models for Communications

Covers mathematical tools for communication systems and data science, including information theory and signal processing.

Estimation and Linear Prediction - Part 2

Explores power spectral density, Wiener-Khintchine theorem, ergodicity, and correlation estimation in random signals for signal processing.

Lecture: Shannon

Covers the basics of information theory, focusing on Shannon's setting and channel transmission.

Error Correction Codes: Theory and Applications

Covers error correction codes theory and applications, emphasizing the importance of minimizing distance for reliable communication.