Independent and memoryless sampling rate distortion

Abstract

Consider a discrete memoryless multiple source with m component sources. A subset of k ≤ m sources are sampled at each time instant and jointly compressed in order to reconstruct all the m sources under a given distortion criterion. A sampling rate distortion function is studied for two main sampling schemes. First, for independent random sampling performed without knowledge of the source outputs, it is shown that the sampling rate distortion function is the same regardless of whether the decoder is informed or not of the sequence of sampling sets. Next, memoryless random sampling is considered with the sampler depending on the source outputs and with an informed decoder. It is shown that deterministic sampling, characterized by a conditional point-mass, is optimal and suffices to achieve the sampling rate distortion function. For memoryless random sampling with an uninformed decoder, an upper bound for the sampling rate distortion function is seen to possess a similar property of conditional point-mass optimality. It is shown by example that memoryless sampling with an informed decoder can outperform strictly any independent random sampler, and that memoryless sampling can do strictly better with an informed decoder than without.