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Codebook
About: Codebook is a research topic. Over the lifetime, 8492 publications have been published within this topic receiving 115995 citations.
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23 Jun 1993TL;DR: The vector quantization codebook and the thresholds are used by a vector quantizer to encode a set of input vectors (V 1 -V TOT ). The determination that a distance between a vector to be encoded and a quantized vector in a codebook is less than the associated threshold causes a search for the closest vector to terminate for a nearest neighbor vector quantifier.
Abstract: Methods and apparatus for vector quantization. A threshold generator generates an i threshold (Threshold i ) to be associated with each i quantized vector of n quantized vectors in a vector quantization codebook. The vector quantization codebook and the thresholds are used by a vector quantizer to encode a set of input vectors (V 1 -V TOT ). The determination that a distance between a vector to be encoded and a quantized vector in a codebook is less than the associated threshold causes a search for the closest vector to terminate for a nearest neighbor vector quantizer. In some embodiments, the vectors comprise samples of continuous signals for sound containing speech, or display signals. In other embodiments, codebook vectors are arranged from most frequently encoded vectors to least frequently encoded vectors.
125 citations
TL;DR: It is demonstrated that power control based on the feedback is instrumental in achieving the D-M tradeoff, and that rate adaptation is important in obtaining a high diversity gain even at high rates.
Abstract: The diversity-multiplexing (D-M) tradeoff in a multi antenna channel with optimized resolution-constrained channel state feedback is characterized. The concept of minimum guaranteed multiplexing gain in the forward link is introduced and shown to significantly influence the optimal D-M tradeoff. It is demonstrated that power control based on the feedback is instrumental in achieving the D-M tradeoff, and that rate adaptation is important in obtaining a high diversity gain even at high rates. A criterion to determine finite-length codes to be tradeoff optimal is presented, leading to a useful geometric characterization of the class of extended approximately universal codes. With codes from this class, the optimal D-M tradeoff is achievable by the combination of a feedback-dependent power controller and a single code-book for single-rate or two codebooks for adaptive-rate transmission. Finally, lower bounds to the optimal D-M tradeoffs based on Gaussian coding arguments are also studied. In contrast to the no-feedback case, these random coding bounds are only asymptotically tight, but can quickly approach the optimal tradeoff even with moderate codeword lengths.
124 citations
TL;DR: An algorithm for automatic image orientation estimation using a Bayesian learning framework is presented and it is demonstrated that a small codebook extracted from a learning vector quantizer can be used to estimate the class-conditional densities of the observed features needed for the Bayesian methodology.
Abstract: We present an algorithm for automatic image orientation estimation using a Bayesian learning framework. We demonstrate that a small codebook (the optimal size of codebook is selected using a modified MDL criterion) extracted from a learning vector quantizer (LVQ) can be used to estimate the class-conditional densities of the observed features needed for the Bayesian methodology. We further show how principal component analysis (PCA) and linear discriminant analysis (LDA) can be used as a feature extraction mechanism to remove redundancies in the high-dimensional feature vectors used for classification. The proposed method is compared with four different commonly used classifiers, namely k-nearest neighbor, support vector machine (SVM), a mixture of Gaussians, and hierarchical discriminating regression (HDR) tree. Experiments on a database of 16 344 images have shown that our proposed algorithm achieves an accuracy of approximately 98% on the training set and over 97% on an independent test set. A slight improvement in classification accuracy is achieved by employing classifier combination techniques.
123 citations
TL;DR: A squared distance criterion for antenna location design in generalized distributed antenna systems (GDAS) is proposed to maximize the cell averaged ergodic capacity and is equivalent to codebook design in vector quantization.
Abstract: A squared distance criterion for antenna location design in generalized distributed antenna systems (GDAS) is proposed to maximize the cell averaged ergodic capacity. The criterion requires the antenna port locations minimize the expectation of the squared distance between a randomly distributed user and the nearest antenna port. This is equivalent to codebook design in vector quantization. For uniform user distribution, we can easily derive analytical expressions for antenna locations. For more general user distribution, we can obtain numerical results using the codebook design algorithm. Applying the proposed criterion to circular-layout GDAS with uniform user distribution and linear cell with non-uniform user distribution, we achieve near optimal performance.
123 citations