We present a constructive approach to the functional quantization problem of stochastic processes, with an emphasis on Gaussian processes. The approach is constructive, since we reduce the infinite-dimensional functional quantization problem to a finite-dimensional quantization problem that can be solved numerically. Our approach achieves the sharp rate of the minimal quantization error and can...

This work addresses joint quantization of adjacent speech parameter values or vectors. The basic joint quantization scheme is improved by using a low-complexity predictor and by allowing the quantizer to operate in several modes. In addition, this paper introduces an efficient algorithm for training quantizers having the proposed structure. The algorithm is used for training a practical quantiz...

In this paper we investigate an algorithm for the suppression of errors caused by quantization of frame coefficients and by erasures in their subsequent transmission. The erasures are assumed to happen independently, modeled by a Bernoulli experiment. The algorithm for error correction in this study embeds check bits in the quantization of frame coefficients, causing a possible, but controlled ...

We introduce a technique for dimensionality estimation based on the notion of quantization dimension, which connects the asymptotic optimal quantization error for a probability distribution on a manifold to its intrinsic dimension. The definition of quantization dimension yields a family of estimation algorithms, whose limiting case is equivalent to a recent method based on packing numbers. Usi...

In this paper, the quality of quantization and visualization of vectors, obtained by vector quantization methods (self-organizing map and neural gas), is investigated. A multidimensional scaling is used for visualization of multidimensional vectors. The quality of quantization is measured by a quantization error. Two numerical measures for proximity preservation (Konig’s topology preservation m...

Optimum scalar quantization is considered for the IIR filter and quantization system presented in "Power reduction in wireless receivers through multistage digital filtering and quantization" [1]. In [1], only suboptimum uniform quantization was used. An optimum scalar quantizer was constructed for a training sequence with a Signal to Interference ratio of −40dB, as was considered in extensivel...

This paper introduces a method to achieve reltive error control in Quantized State System (QSS) methods. Based on the use of logarithmic quantization, the proposed methodology solves the problem of quantum selection. Keywords— Quantization Based Integration, Continuous System Simulation.

This thesis devises quantization and source-channel coding schemes to increase the error robustness of the newly standardized ITU-T G.711.1 speech coder. The schemes employ Gaussian mixture model (GMM) based multiple description quantizers (MDQ). The thesis reviews the literature focusing on GMM based quantization, MDQ, and GMM-MDQ design methods and bit allocation schemes. GMM-MDQ are then des...

Quantization, which maps real values of raw data to a series of fixed gray levels, is an inevitable step in Optical Coherence Tomography (OCT) image formation. Three new quantization methods, Minimum Distortion, Information Expansion and Maximum Entropy are applied in the specific problem. Quantization results of a capillary with milk and the femoralis of rabbit are shown in this paper. Compari...

Quantization is a necessary intermediate step in any digital processing device. The Memoryless Scalar quantization and the Sigma Delta quantization are two well known quantization schemes with different emphasis. In this talk, I will discuss the quantization problem raised in frame theory and compressed sensing, and explain the benefit that Sigma Delta quantization can deliver. In particular, w...