The author establishes notation conventions for the paper, ensuring consistency throughout.
Section III: Formalizing the Challenge of Computing Channel Capacity
The paper rigorously formalizes the challenge of computing channel capacity for discrete memoryless channels (DMCs). The author explains the fundamental obstacle in calculating this capacity using a compelling analogy with evolutionary game theory.
Section IV: Recovering the Blahut-Arimoto Algorithm
The author demonstrates how the updating map in the Blahut-Arimoto algorithm can be recovered by discretizing the flow associated with an ODE (ordinary differential equation). This connection to continuous-time systems provides a new perspective on the BAA. The author also highlights the relationship between the Baum-Eagon map and its continuous-time counterpart, which has been recently generalized.
Section V: Conclusion
The paper concludes by summarizing the main findings and their implications for understanding information processing in both continuous-time and discrete-time systems. The author emphasizes the significance of this connection for developing more efficient algorithms and deepening our comprehension of fundamental principles in information theory.
