N. Farvardin

Publications134
h-index34
Citations5,294
Highly Influential Citations308
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  • Publications
  • Influence
A study of vector quantization for noisy channels
  • N. Farvardin
  • Mathematics, Computer Science
  • IEEE Trans. Inf. Theory
  • 1 July 1990
TLDR
Several issues related to vector quantization for noisy channels are discussed. Expand
  • 522
  • 40
On the performance and complexity of channel-optimized vector quantizers
TLDR
The performance and complexity of channel-optimized vector quantizers are studied for the Gauss-Markov source. Expand
  • 311
  • 30
Optimal quantizer design for noisy channels: An approach to combined source - channel coding
TLDR
We present an analysis of the zero-memory quantization of memoryless sources when the quantizer output is to be encoded and transmitted across a noisy channel. Expand
  • 371
  • 29
Progressive transmission of images over memoryless noisy channels
TLDR
An embedded source code allows the decoder to reconstruct the source progressively from the prefixes of a single bit stream. Expand
  • 227
  • 29
Optimum quantizer performance for a class of non-Gaussian memoryless sources
TLDR
The performance of optimum quantizers subject to an entropy constraint is studied for a wide class of memoryless sources. Expand
  • 363
  • 15
Three-dimensional subband coding of video
TLDR
We describe and show the results of video coding based on a three-dimensional (3-D) spatio-temporal subband decomposition. Expand
  • 297
  • 13
Subband Image Coding Using Entropy-Coded Quantization over Noisy Channels
TLDR
Under the assumption of noiseless transmission the authors develop two entropy-coded subband image coding schemes. Expand
  • 214
  • 13
Flat Zones Filtering, Connected Operators, and Filters by Reconstruction
  • 192
  • 13
Comparison of different methods of classification in subband coding of images
TLDR
This paper investigates various classification techniques, applied to subband coding of images, as a way of exploiting the nonstationary nature of image subbands. Expand
  • 181
  • 11
  • PDF
Robust and efficient quantization of speech LSP parameters using structured vector quantizers
TLDR
Three robust algorithms based on the recently proposed concept of structured vector quantization have been developed for quantization of speech LSP (line spectrum pair) parameters. Expand
  • 139
  • 8