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» Asymptotically Optimal Model Estimation for Quantization
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ICMCS
2006
IEEE
105views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Entropy and Memory Constrained Vector Quantization with Separability Based Feature Selection
An iterative model selection algorithm is proposed. The algorithm seeks relevant features and an optimal number of codewords (or codebook size) as part of the optimization. We use...
Sangho Yoon, Robert M. Gray
ICASSP
2009
IEEE
14 years 2 months ago
A mixed time-scale algorithm for distributed parameter estimation : Nonlinear observation models and imperfect communication
Abstract— The paper considers the algorithm NLU for distributed (vector) parameter estimation in sensor networks, where, the local observation models are nonlinear, and inter-sen...
Soummya Kar, José M. F. Moura
ICIP
2004
IEEE
14 years 9 months ago
Estimation of attacker's scale and noise variance for qim-dc watermark embedding
Quantization-based watermarking schemes are vulnerable to amplitude scaling. Therefore, the scaling factor needs to be estimated at the decoder side, such that the received (attac...
Reginald L. Lagendijk, Ivo D. Shterev
DAC
2000
ACM
13 years 12 months ago
An asymptotically constant, linearly bounded methodology for the statistical simulation of analog circuits including component m
Abstract: This paper presents a new statistical methodology to simulate the effect of both inter-die and intra-die variation on the electrical performance of analog integrated circ...
Carlo Guardiani, Sharad Saxena, Patrick McNamara, ...
NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 7 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin