Source Coding for Quasiarithmetic Penalties

Whereas Huffman coding finds a prefix code minimizing mean codeword length for a given finite-item probability distribution, quasiarithmetic or quasilinear coding problems have the goal of minimizing a generalized mean of the form rho^-1(Sigma_ip_irho(l_i )), where l_i denotes the length of the ith codeword, p _i denotes the corresponding probability, and rho is a monotonically increasing cost function. Such problems, proposed by Campbell, have a number of diverse applications. Several cost functions are shown here to yield quasiarithmetic problems with simple redundancy bounds in terms of a generalized entropy. A related property, also shown here, involves the existence of optimal codes: For "well-behaved" cost functions, optimal codes always exist for (possibly infinite-alphabet) sources having finite generalized entropy. An algorithm is introduced for finding binary codes optimal for convex cost functions. This algorithm, which can be extended to other minimization utilities, can be performed using quadratic time and linear space. This reduces the computational complexity of a problem involving minimum delay in a queue, allows combinations of previously considered problems to be optimized, and greatly expands the set of problems solvable in quadratic time and linear space