Trellis source codes designed by conjugate gradient optimization

Time-invariant trellis codes for stationary, ergodic, discrete-time sources are designed by unconstrained, nonlinear optimization of the performance in a simulated source encoding with the Viterbi algorithm. A nonderivative conjugate directions algorithm and a conjugate gradient algorithm with restarts are applied to design low-constraint-length, unit-rate, binary codes for the memoryless Gaussian source. The latter algorithm is also used to design codes for the memoryless Laplacian source and a third-order autoregressive model for speech. Good codes are tabulated and compared to other known results on a performance versus complexity basis. Those for the Gaussian source are tested in a joint (tandem) trellis-coding system with known convolutional channel codes