Coding theorems of information theory

1.Heuristic Introduction to the Discrete Memoryless Channel 2.Combinatorial Preliminaries 2.1.Generated sequences 2.2.Properties of the entropy function Remarks 3.The Discrete Memoryless Channel 3.1.Description of the channel 3.2.A coding theorem 3.3.The strong converse 3.4.Strong converse for the binary symmetric channel 3.5.The finite-state channel with state calculable by both sender and receiver 3.6.The finite-state channel with state calculable only by the sender Remarks 4.Compound Channels 4.1.Introduction 4.2.The canonical channel 4.3.A coding theorem 4.4.Strong converse 4.5.Compound d.m.c. with c.p.f. known only to the receiver or only to the sender 4.6.Channels where the c.p.f. for each letter is stochastically determined 4.7.Proof of Theorem 4.6.4. 4.8.The d.m.c. with feedback Remarks 5.The Discrete Finite-Memory Channel 5.1.The discrete channel 5.2.The discrete finite-memory channel 5.3.The coding theorem for the d.f.m.c. 5.4.Strong converse of the coding theorem for the d.f.m.c. 5.5.Rapidity of approach to C in the d.f.m.c. 5.6.Discussion of the d.f.m.c. Remarks 6.Channels with Arbitrarily Varying Channel Probability Functions 6.1.Introduction 6.2.Necessary and sufficient conditions for a positive rate of transmission 6.3. Remarks on the capacity of an arbitrarily varying channel 6.4.The capacity C of an arbitrarily varying channel when b=2 6.5.Certain results for the general arbitrarily varying channel Remarks 7.General Discrete Channels 7.1.Alternative description of the general discrete channel 7.2.The method of maximal codes 7.3.The method of random codes 7.4.Weak converses 7.5.Digression on the d.m.c. 7.6.Discussion of the foregoing 7.7.Channels without a capacity 7.8.Strong converses 7.9.The strong converse for the d.m.c. revisited Remarks 8.The Semi-Continuous Memoryless Channel