Results 51 to 60 of about 178,882 (183)
Improving learning vector quantization using data reduction
IJAIN (International Journal of Advances in Intelligent Informatics), 2019 Learning Vector Quantization (LVQ) is a supervised learning algorithm commonly used for statistical classification and pattern recognition. The competitive layer in LVQ studies the input vectors and classifies them into the correct classes. The amount of
Pande Nyoman Ariyuda Semadi +1 more
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Handwriting Character Recognition using Vector Quantization Technique
Knowledge Engineering and Data Science, 2019 This paper seeks to explore Learning Vector Quantization (LVQ) processing stage to recognize The Buginese Lontara script from Makassar as well as explaining its accuracy. The testing results of LVQ obtained an accuracy degree of 66.66 %. The most optimal
Haviluddin Haviluddin +5 more
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Hybrid vector quantization [PDF]
Optical Engineering, 1993 Vector quantization (VQ) is a powerful technique for low-bit-rate image coding. However, initial studies of image coding with VQ have revealed that VQ causes degradations, most notably around edges. Moreover, the computational complexity is high. Although a few algorithms have been developed to reduce edge degradation, such as block truncation coding ...
openaire +1 more source
One-pass adaptive universal vector quantization [PDF]
, 1994 The authors introduce a one-pass adaptive universal quantization technique for real, bounded alphabet, stationary sources. The algorithm is set on line without any prior knowledge of the statistics of the sources which it might encounter and ...
Chou, P. A., Effros, M., Gray, R. M.
core
On Optimal Zero-Delay Coding of Vector Markov Sources
, 2014 Optimal zero-delay coding (quantization) of a vector-valued Markov source driven by a noise process is considered. Using a stochastic control problem formulation, the existence and structure of optimal quantization policies are studied.
Linder, Tamás, Yüksel, Serdar
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Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model
The Scientific World Journal, 2014 Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages,
Lokesh Selvaraj, Balakrishnan Ganesan
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Distributed Vector Quantization Based on Kullback-Leibler Divergence
Entropy, 2015 The goal of vector quantization is to use a few reproduction vectors to represent original vectors/data while maintaining the necessary fidelity of the data.
Pengcheng Shen +2 more
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Unified Treatment of Mixed Vector-Scalar Screened Coulomb Potentials for Fermions
, 2007 The problem of a fermion subject to a general mixing of vector and scalar screened Coulomb potentials in a two-dimensional world is analyzed and quantization conditions are found.Comment: 7 ...
A. S. DE CASTRO +2 more
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Text-Independent Speaker Verification Based on Information Theoretic Learning [PDF]
Mehran University Research Journal of Engineering and Technology, 2011 In this paper VQ (Vector Quantization) based on information theoretic learning is investigated for the task of text-independent speaker verification. A novel VQ method based on the IT (Information Theoretic) principles is used for the task of speaker ...
Sheeraz Memon +2 more
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During the past ten years Vector Quantization (VQ) has developed from a theoretical possibility promised by Shannon's source coding theorems into a powerful and competitive technique for speech and image coding and compression at medium to low bit rates.
Gray, Robert M.
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