Channel Capacity and Coding Theorems

About this course

Derive channel capacity for discrete memoryless channels, prove Shannon's noisy-channel coding theorem, and analyze capacity of Gaussian channels.

• 20 lessons
• 2 h
• advanced

What you'll learn

• Explain the importance of channel capacity in communication systems
• Describe the scope and goals of the course
• Define random variables and probability distributions
• Compute expectations and conditional probabilities
• Define entropy and conditional entropy
• Calculate entropy for simple distributions

Finishing the course

• 80 knowledge-check questions along the way, so you know the ideas stuck before you move on.
• Watching is free and needs no account. Sign in to save your progress. Pass each lesson's quiz (60%+) to earn the certificate. Each certificate has its own public verification link to share, marked quiz-verified.

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