vector quantization

[¦vek·tər ‚kwän·tə′zā·shən]

(computer science)

A data compression technique in which a finite sequence of values is presented as resembling the template (from among the choices available to a given codebook) that minimizes a distortion measure.

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References in periodicals archive

Nahavandi, "Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization," Journal of Intelligent Manufacturing, vol.

Applying Two-Stage Neural Network Based Classifiers to the Identification of Mixture Control Chart Patterns for an SPC-EPC Process

Vector Quantization (VQ) is highly competitive technique for automatic speaker identification compared with Gaussian Mixture Model (GMM) (Kinnunen et al.

COMBINING FEATURES AT VECTOR LEVELFOR HIGHER SPEED AND ACCURACY OF SPEAKER IDENTIFICATION

In this paper, we consider distributed vector quantization. When using a sensor network as an exploratory infrastructure, we need to transmit and store the data collected by sensors.

Distributed vector quantization over sensor network

Genetic Algorithm and Vector Quantization. The vector quantization (VQ) approach is used for mapping vectors (feature extraction of input signal) from a large vector space to a finite number of regions in that space.

Enhancing speech recognition using improved particle swarm optimization based hidden Markov model

In this model, with vector quantization (VQ), descriptor size can be reduced significantly; for example, in the test model (Francini et al.

Learning compact visual descriptors for low bit rate mobile landmark search

Applications to Pulse Code Modulation and Vector Quantization of Images are addressed.

Geometric approach to sampling and communication

Linear Vector Quantization using Bit Mapping: In Bit-mapping LVQ the segmented characters are directly fed as an input to Neural Network for training.

Comparison of neural network training algorithms for handwriting recognition and scope for optimization