Designing Convolutional Codes

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Explores binary channel decoding and vector spaces in coding theory.

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

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

Explores encoding and decoding techniques in communication systems, focusing on fundamental limits and mutual information computations.

Covers the design and analysis of signal constellations in communication systems.

Explores random coding achievability and proof variants in information theory, emphasizing achievable rates and architectural principles.

Explores error correction codes, decoding algorithms, and their role in communication systems.

Covers expected code word length, Huffman procedure, and entropy in coding theory.

Covers Convolutional Codes, Viterbi Algorithm, state and branch metric computations, and survivor path length limitations.

Explores interpolation spaces in Banach spaces, emphasizing real continuous interpolation spaces and the K-method.