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Ph D Thesis On Vector Quantization
The University of Melbourne Library. Open to the public Thesis English Show 0 more libraries None of your libraries hold this item.
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- Levrard : Fast rates for empirical vector quantization.
Add a tag Cancel Be the first to add a tag for this edition. Lists What are lists? Login to add to list. Vector quantization has been initially developed in the early 50's.
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The aim was to optimize the transmission of stationary signals. In this context, quantization was a process of signal discretization. A large part of this work has been done in Bell laboratories.
Having long been confined to signal processing, optimal quantization rose in the mids the interest of several research teams in probability in France LPMA-UMR Univ. Quantization methods now have their place in numerical probability, especially for solving problems arising in mathematical finance such as:.
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- [email protected]: Vector quantization based efficient still image compression algorithms?
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The research and the development in the field of vector quantization finite-dimensional signals continues today, mainly in connection with applications in signal processing and numerical probabilities. The explosion of computing capabilities in recent decades has both been a motivation and a driving force behind the development of such numerical methods. Meanwhile, a new field emerged last decade under the name "functional quantization".
This is to extend the concept to the infinite dimensional setting. Our customer support agent will call you back within 15 minutes. Sign up to our newsletter to receive a promo code. Receive discount.
Subspace distortion measurement techniques for spatial domain image vector quantization
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