Sharif Digital Repository

New inner and outer bounds on the achievable compression-equivocation rate region for generalised secure data compression with side information are given that do not match in general. In this setup, two senders, Alice and Charlie intend to transmit information to Bob via channels with limited capacity so that he can reliably reconstruct their observations. The eavesdropper, Eve, has access to one of the channels at each instant and is interested in the source of the same channel at the time. Bob and Eve also have their own observations, which are correlated with Alice's and Charlie's observations. In this model, two equivocation and compression rates are defined with respect to the sources... 

The voice channels present in cellular communication networks provide reliable, widespread and high priority communication mediums. Using these voice channels as a bearer for data transmission allows to deliver high Quality of Service data. But voice channels include vocoders that hinder the data flow by compressing the waveforms prior to transmission. Calculating vocoder channel capacity remains a challenging problem since no analytical model has been proposed for the vocoder channel so far. In this research, simplified models for the vocoder channel are proposed and bounds on vocoder channel capacity are derived based on them. In common cellular networks, the vocoder compression rate is... 

This study presents the utilisation of neural-network for bi-level image compression. In the proposed lossy compression method, the locations of pixels of image are applied to the inputs of a multilayer perceptron neural-network. The output of the network denotes the pixel intensity (0 or 1). The final weights of the trained neural-network are quantised, represented by a few bits, Huffman encoded and then stored as the compressed image. In the decompression phase, by applying the pixels locations to the trained network, the output determines the intensity. The results of experiments on more than 4000 different images indicate higher compression rate of the proposed structure compared with... 

The Renyi's information dimension (RID) of an n-dimensional random vector (RV) is the average dimension of the vector when accounting for non-zero probability measures over lower-dimensional subsets. From an information-theoretical perspective, the RID can be interpreted as a measure of compressibility of a probability distribution. While the RID for continuous and discrete measures is well understood, the case of a discrete-continuous measures presents a number of interesting subtleties. In this paper, we investigate the RID for a class of multi-dimensional discrete-continuous random measures with singularities on affine lower dimensional subsets. This class of RVs, which we term affinely...