2 citations · 7 across the 6 of their papers we have counts for
6 papers
Lossy Source Compression of Non-Uniform Binary Sources Using GQ-LDGM Codes
Lorenzo Cappellari
In this paper, we study the use of GF(q)-quantized LDGM codes for binary source coding. By employing quantization, it is possible to obtain binary codewords with a non-uniform dist…
On Syndrome Decoding for Slepian-Wolf Coding Based on Convolutional and Turbo Codes
Lorenzo Cappellari
In source coding, either with or without side information at the decoder, the ultimate performance can be achieved by means of random binning. Structured binning into cosets of per…
On Superposition Coding for the Wyner-Ziv Problem
Lorenzo Cappellari
In problems of lossy source/noisy channel coding with side information, the theoretical bounds are achieved using "good" source/channel codes that can be partitioned into "good" ch…
A Unified Perspective on Parity- and Syndrome-Based Binary Data Compression Using Off-the-Shelf Turbo Codecs
Lorenzo Cappellari, Andrea De Giusti
We consider the problem of compressing memoryless binary data with or without side information at the decoder. We review the parity- and the syndrome-based approaches and discuss t…
Distributed Source Coding Using Continuous-Valued Syndromes
Lorenzo Cappellari
This paper addresses the problem of coding a continuous random source correlated with another source which is only available at the decoder. The proposed approach is based on the e…
Trellis-Coded Quantization Based on Maximum-Hamming-Distance Binary Codes
Lorenzo Cappellari
Most design approaches for trellis-coded quantization take advantage of the duality of trellis-coded quantization with trellis-coded modulation, and use the same empirically-found…