Results 11 - 20 of 2,535

Efficient vector quantization of LPC parameters at 24 bitdframe

by Kuldip K. Paliwal, Bishnu S Atal - J. Acoust. Soc. Amer , 1990
"... Abstruct- Linear predictive coding (LPC) parameters are widely used in various speech processing applications for representing the spectral envelope information of speech. For low bit rate speech-coding applications, it is important to quantize these parameters accurately using as few bits as possib ..."
Abstract - Cited by 141 (9 self) - Add to MetaCart
Abstruct- Linear predictive coding (LPC) parameters are widely used in various speech processing applications for representing the spectral envelope information of speech. For low bit rate speech-coding applications, it is important to quantize these parameters accurately using as few bits

Trace inference, curvature consistency, and curve detection

by Pierre Parent, Steven W. Zucker - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1989
"... We describe a novel approach to curve inference based on curvature information. The inference procedure is divided into two stages: a trace inference stage, to which this paper is devoted, and a curve synthesis stage, which will be treated in a separate paper. It is shown that recovery of the trace ..."
Abstract - Cited by 241 (15 self) - Add to MetaCart
curvature esti-mates, in terms of a curvature consistency relation. Because all curve information is quantized, special care must be taken to obtain accurate estimates of trace points, tangents and curvatures. This issue is ad-dressed specifically by the introduction of a smoothness constraint and a maximum

Lattice Quantization with Side Information

by Sergio D. Servetto , 2000
"... We consider the design of lattice vector quantizers for the problem of coding Gaussian sources with uncoded side information available only at the decoder. The design of such quantizers can be reduced to the problem of finding an appropriate sublattice of a given lattice codebook. We study the pe ..."
Abstract - Cited by 32 (3 self) - Add to MetaCart
We consider the design of lattice vector quantizers for the problem of coding Gaussian sources with uncoded side information available only at the decoder. The design of such quantizers can be reduced to the problem of finding an appropriate sublattice of a given lattice codebook. We study

MIMO Broadcast Channels With Finite-Rate Feedback

by Nihar Jindal , 2006
"... Multiple transmit antennas in a downlink channel can provide tremendous capacity (i.e., multiplexing) gains, even when receivers have only single antennas. However, receiver and transmitter channel state information is generally required. In this correspondence, a system where each receiver has per ..."
Abstract - Cited by 189 (1 self) - Add to MetaCart
perfect channel knowledge, but the transmitter only receives quantized information regarding the channel instantiation is analyzed. The well-known zero-forcing transmission technique is considered, and simple expressions for the throughput degradation due to finite-rate feedback are derived. A key finding

Supervised Learning of Quantizer Codebooks by Information Loss Minimization

by Svetlana Lazebnik, Maxim Raginsky , 2007
"... This paper proposes a technique for jointly quantizing continuous features and the posterior distributions of their class labels based on minimizing empirical information loss, such that the index K of the quantizer region to which a given feature X is assigned approximates a sufficient statistic fo ..."
Abstract - Cited by 71 (0 self) - Add to MetaCart
This paper proposes a technique for jointly quantizing continuous features and the posterior distributions of their class labels based on minimizing empirical information loss, such that the index K of the quantizer region to which a given feature X is assigned approximates a sufficient statistic

Distributed average consensus with dithered quantization

by Tuncer C. Aysal, Mark J. Coates, Michael G. Rabbat - the IEEE Transactions of Signal Processing , 2008
"... In this paper, we develop algorithms for distributed computation of averages of the node data over networks with bandwidth/power constraints or large volumes of data. Distributed averaging algorithms fail to achieve consensus when deterministic uniform quantization is adopted. We propose a distribut ..."
Abstract - Cited by 52 (1 self) - Add to MetaCart
distributed algorithm in which the nodes utilize probabilistically quantized information, i.e., dithered quantization, to communicate with each other. The algorithm we develop is a dynamical system that generates sequences achieving a consensus at one of the quantization values almost surely. In addition, we

Quantized Indexing: Background Information *

by Ratko V. Tomic , 2005
"... This report presents background material ‡ for the Quantized Indexing § (QI) form of enumerative coding. Following the introduction to conventional enumerative coding and its reformulation as lattice walks, the relations between arithmetic and enumerative coding are explored. In addition to examinin ..."
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This report presents background material ‡ for the Quantized Indexing § (QI) form of enumerative coding. Following the introduction to conventional enumerative coding and its reformulation as lattice walks, the relations between arithmetic and enumerative coding are explored. In addition

Distributed Subgradient Methods and Quantization Effects

by Angelia Nedić, Alex Olshevsky, Asuman Ozdaglar, John N. Tsitsiklis
"... We consider a convex unconstrained optimization problem that arises in a network of agents whose goal is to cooperatively optimize the sum of the individual agent objective functions through local computations and communications. For this problem, we use averaging algorithms to develop distributed ..."
Abstract - Cited by 15 (1 self) - Add to MetaCart
distributed subgradient methods that can operate over a time-varying topology. Our focus is on the convergence rate of these methods and the degradation in performance when only quantized information is available. Based on our recent results on the convergence time of distributed averaging algorithms, we

Conversation Quantization for Informal Information Circulation

by Hidekazu Kubota, Ken Saitoh, Ken Kumagai, Yohei Kawaguchi, Satoshi Nomura, Yasuyuki Sumi, Toyoaki Nishida - in a Community, The Fourth International Workshop on Social Intelligence Design (SID 2005
"... Abstract. In this paper, we present a computational approach to understanding and augmenting the conversational knowledge process that is a collective activity for knowledge creation, management, and application, where conversational communications are used as a primary means of interaction among pa ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
participating agents. The key idea is conversation quantization, a technique of approximating a continuous flow of conversation by a series of conversation quanta that represent points of the discourse. Conversation quantization enables to implement a rather robust conversation system by basing it on a large

Distributed average consensus using probabilistic quantization

by Tuncer C. Aysal, Mark Coates, Michael Rabbat , 2007
"... In this paper, we develop algorithms for distributed computation of averages of the node data over networks with bandwidth/power constraints or large volumes of data. Distributed averaging algorithms fail to achieve consensus when deterministic uniform quantization is adopted. We propose a distribut ..."
Abstract - Cited by 52 (6 self) - Add to MetaCart
distributed algorithm in which the nodes utilize probabilistically quantized information to communicate with each other. The algorithm we develop is a dynamical system that generates sequences achieving a consensus, which is one of the quantization values. In addition, we show that the expected value
Results 11 - 20 of 2,535