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OPTIMAL MODULATION POLICIES FOR DISCRETE TIME PROCESSES
A Summary of Previous Work
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a_(s a+(s amplitude modulation Appendix Assumption average power constraint average-power constraints Baire function channel capacity Chapter constraint is satisfied continuous-time Markov process contraction mapping decision boundaries defined depends detection interval dynamic programming energy to decision error Pr(E existence of optimal expected cost feedback link finite number first-passage function of initial H is true hence implies INITIAL LOG-LIKELIHOOD RATIO INITIAL PROBABILITY minimize the expected minimum cost minimum expected energy modulation level noiseless feedback noisy feedback normalized minimum expected Note optimal modulation policies optimal policies optimal stationary Markov optimality equation optimum ordinary differential equation peak-power and average-power peak-power constraint Pr(FA Pr(Miss probability distribution probability of error radar and communication ratio of H receiver satisfies the optimality shown signal design problem sinh solution spectral density stationary modulation policies stationary policies tanh d/2 total expected transmitter Turin white Gaussian noise white noise