Browsing by Author "Hsu, HI"

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Constrained VQ codebook design for noisy channels
(2001-05-10)
Chang, WW
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Hsu, HI
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電信工程研究所
;
Institute of Communications Engineering
A codebook design approach for constrained vector quantisation using the Hadamard transform of channel transition probabilities is proposed. It is examined for quantisation of Gauss-Markov sources over channels with memory and compared with the generalised Lloyd algorithm.
Index assignment in vector quantisation for channels with memory
(2002-06-01)
Chang, WW
;
Hsu, HI
;
電信工程研究所
;
Institute of Communications Engineering
The study presents a formulation of a Hadamard framework for analysing the vector quantisation over channels with memory. In seeking faster response, classes of index assignments are defined in terms of the Hadamard transform of channel transition probabilities. An index assignment algorithm is developed that achieves high robustness against channel errors, and its performance in vector quantisation of Gauss-Markov sources under noisy channel conditions is illustrated.
MMSE decoding for vector quantization over channels with memory
(2002)
Hsu, HI
;
Chang, WW
;
Liu, XB
;
Koh, SN
;
電信工程研究所
This paper presents memory-enhanced extensions of minimum mean-squared error (MMSE) decoding for vector quantization over noisy channels. We also develop a recursive algorithm for computing the transition probabilities of the Gilbert channel, and illustrate its performance in vector quantization of Gauss-Markov sources under noisy channel conditions. Simulation results indicate that the proposed algorithm enables the implementation of an MMSE decoder with increased robustness to channel errors.
The automated cryptanalysis of DFT-based speech scramblers
(2000-12-01)
Chang, WW
;
Hsu, HI
;
電信工程研究所
;
Institute of Communications Engineering
An automated method For cryptanalysis of DFT-based analog speech scramblers is presented through statistical estimation treatments. In the proposed system, the cipher-text only attack is formulated as a combinatorial optimization problem leading to a search for the most likely key estimate. For greater efficiency, we also explore the benefits of genetic algorithm to develop an estimation method which takes into account the doubly stochastic characteristics of the underlying keyspace. Simulation results: indicate that the global explorative properties of genetic algorithms make them very effective at estimating the most likely permutation and by using this estimate significant amount of the intelligibility can be recovered from the ciphertext following the attack on DFT-based speech scramblers.