Results 1  10
of
40
Closest Point Search in Lattices
 IEEE TRANS. INFORM. THEORY
, 2000
"... In this semitutorial paper, a comprehensive survey of closestpoint search methods for lattices without a regular structure is presented. The existing search strategies are described in a unified framework, and differences between them are elucidated. An efficient closestpoint search algorithm, ba ..."
Abstract

Cited by 194 (1 self)
 Add to MetaCart
In this semitutorial paper, a comprehensive survey of closestpoint search methods for lattices without a regular structure is presented. The existing search strategies are described in a unified framework, and differences between them are elucidated. An efficient closestpoint search algorithm, based on the SchnorrEuchner variation of the Pohst method, is implemented. Given an arbitrary point x 2 R m and a generator matrix for a lattice , the algorithm computes the point of that is closest to x. The algorithm is shown to be substantially faster than other known methods, by means of a theoretical comparison with the Kannan algorithm and an experimental comparison with the Pohst algorithm and its variants, such as the recent ViterboBoutros decoder. The improvement increases with the dimension of the lattice. Modifications of the algorithm are developed to solve a number of related search problems for lattices, such as finding a shortest vector, determining the kissing number, compu...
Stochastic Power Control for Cellular Radio Systems
 IEEE Trans. Commun
, 1997
"... For wireless communication systems, iterative power control algorithms have been proposed to minimize transmitter powers while maintaining reliable communication between mobiles and base stations. To derive deterministic convergence results, these algorithms require perfect measurements of one or mo ..."
Abstract

Cited by 89 (8 self)
 Add to MetaCart
For wireless communication systems, iterative power control algorithms have been proposed to minimize transmitter powers while maintaining reliable communication between mobiles and base stations. To derive deterministic convergence results, these algorithms require perfect measurements of one or more of the following parameters: (i) the mobile's signal to interference ratio (SIR) at the receiver, (ii) the interference experienced by the mobile, and (iii) the bit error rate. However, these quantities are often difficult to measure and deterministic convergence results neglect the effect of stochastic measurements. In this work, we develop distributed iterative power control algorithms that use readily available measurements. Two classes of power control algorithms are proposed. Since the measurements are random, the proposed algorithms evolve stochastically and we define the convergence in terms of the mean squared error (MSE) of the power vector from the optimal power vector that is t...
Generalized multiple description coding with correlating transforms
 IEEE Trans. Inform. Theory
, 2001
"... Abstract—Multiple description (MD) coding is source coding in which several descriptions of the source are produced such that various reconstruction qualities are obtained from different subsets of the descriptions. Unlike multiresolution or layered source coding, there is no hierarchy of descriptio ..."
Abstract

Cited by 61 (2 self)
 Add to MetaCart
Abstract—Multiple description (MD) coding is source coding in which several descriptions of the source are produced such that various reconstruction qualities are obtained from different subsets of the descriptions. Unlike multiresolution or layered source coding, there is no hierarchy of descriptions; thus, MD coding is suitable for packet erasure channels or networks without priority provisions. Generalizing work by Orchard, Wang, Vaishampayan, and Reibman, a transformbased approach is developed for producing descriptions of antuple source,. The descriptions are sets of transform coefficients, and the transform coefficients of different descriptions are correlated so that missing coefficients can be estimated. Several transform optimization results are presented for memoryless Gaussian sources, including a complete solution of the aP, aPcase with arbitrary weighting of the descriptions. The technique is effective only when independent components of the source have differing variances. Numerical studies show that this method performs well at low redundancies, as compared to uniform MD scalar quantization. Index Terms—Erasure channels, integertointeger transforms, packet networks, robust source coding.
Weighted Linear Cue Combination with Possibly Correlated Error
 AMERICAN DOCUMENTATION
, 2003
"... We test hypotheses concerning human cue combination in a slant estimation task. Observers ..."
Abstract

Cited by 20 (9 self)
 Add to MetaCart
We test hypotheses concerning human cue combination in a slant estimation task. Observers
Reduced complexity MMSE detection for BLAST architectures
 in Proc. IEEE Global Telecommun. Conf. (IEEE GLOBECOM
"... Abstract — Theoretical and experimental studies have shown that layered spacetime architectures like the BLAST system can exploit the capacity advantage of multiple antenna systems in richscattering environments. In this paper, we present a new efficient algorithm for detecting such architectures ..."
Abstract

Cited by 20 (6 self)
 Add to MetaCart
Abstract — Theoretical and experimental studies have shown that layered spacetime architectures like the BLAST system can exploit the capacity advantage of multiple antenna systems in richscattering environments. In this paper, we present a new efficient algorithm for detecting such architectures with respect to the MMSE criterion. This algorithm utilizes a sorted QR decomposition of the channel matrix and leads to a simple successive detection structure. The algorithm needs only a fraction of computational effort compared to the standard VBLAST algorithm and achieves the same bit error performance. Index Terms — BLAST, MIMO systems, ZeroForcing and MMSE detection, wireless communication. I.
The Shape of Fuzzy Sets in Adaptive Function Approximation
, 2001
"... The shape of ifpart fuzzy sets affects how well feedforward fuzzy systems approximate continuous functions. We explore a wide range of candidate ifpart sets and derive supervised learning laws that tune them. Then we test how well the resulting adaptive fuzzy systems approximate a battery of test ..."
Abstract

Cited by 19 (3 self)
 Add to MetaCart
The shape of ifpart fuzzy sets affects how well feedforward fuzzy systems approximate continuous functions. We explore a wide range of candidate ifpart sets and derive supervised learning laws that tune them. Then we test how well the resulting adaptive fuzzy systems approximate a battery of test functions. No one set shape emerges as the best shape. The sinc function often does well and has a tractable learning law. But its undulating sidelobes may have no linguistic meaning. This suggests that the engineering goal of functionapproximation accuracy may sometimes have to outweigh the linguistic or philosophical interpretations of fuzzy sets that have accompanied their use in expert systems. We divide the ifpart sets into two large classes. The first class consists ofdimensional joint sets that factor into scalar sets as found in almost all published fuzzy systems. These sets ignore the correlations among vector components of input vectors. Fuzzy systems that use factorable ifpart sets suffer in general from exponential rule explosion in high dimensions when they blindly approximate functions without knowledge of the functions. The factorable fuzzy sets themselves also suffer from what we call the second curse of dimensionality: The fuzzy sets tend to become binary spikes in high dimension. The second class of ifpart sets consists of the more general but less commondimensional joint sets that do not factor into scalar fuzzy sets. We present a method for constructing such unfactorable joint sets from scalar distance measures. Fuzzy systems that use unfactorable ifpart sets need not suffer from exponential rule explosion but their increased complexity may lead to intractable learning laws and inscrutable ifthen rules. We prove that some of these unfactorable join...
A generalized subspace approach for enhancing speech corrupted by colored noise
 IEEE TRANS. SPEECH AUDIO PROC
, 2003
"... A generalized subspace approach is proposed for enhancement of speech corrupted by colored noise. A nonunitary transform, based on the simultaneous diagonalization of the clean speech and noise covariance matrices, is used to project the noisy signal onto a signalplusnoise subspace and a noise sub ..."
Abstract

Cited by 19 (5 self)
 Add to MetaCart
A generalized subspace approach is proposed for enhancement of speech corrupted by colored noise. A nonunitary transform, based on the simultaneous diagonalization of the clean speech and noise covariance matrices, is used to project the noisy signal onto a signalplusnoise subspace and a noise subspace. The clean signal is estimated by nulling the signal components in the noise subspace and retaining the components in the signal subspace. The applied transform has builtin prewhitening and can therefore be used in general for colored noise. The proposed approach is shown to be a generalization of the approach proposed by Ephraim and Van Trees for white noise. Two estimators were derived based on the nonunitary transform, one based on timedomain constraints and one based on spectral domain constraints. Objective and subjective measures demonstrated improvements over other subspacebased methods when tested with TIMIT sentences corrupted with speechshaped noise and multitalker babble.
An Attacker’s View of Distance Preserving Maps for Privacy Preserving Data Mining
 Proc. PKDD
, 2006
"... Abstract. We examine the effectiveness of distance preserving transformations in privacy preserving data mining. These techniques are potentially very useful in that some important data mining algorithms can be efficiently applied to the transformed data and produce exactly the same results as if ap ..."
Abstract

Cited by 19 (1 self)
 Add to MetaCart
Abstract. We examine the effectiveness of distance preserving transformations in privacy preserving data mining. These techniques are potentially very useful in that some important data mining algorithms can be efficiently applied to the transformed data and produce exactly the same results as if applied to the original data e.g. distancebased clustering, knearest neighbor classification. However, the issue of how well the original data is hidden has, to our knowledge, not been carefully studied. We take a step in this direction by assuming the role of an attacker armed with two types of prior information regarding the original data. We examine how well the attacker can recover the original data from the transformed data and prior information. Our results offer insight into the vulnerabilities of distance preserving transformations. 1
SuperResolution From Unregistered and Totally Aliased Signals Using Subspace Methods
, 2007
"... In many applications, the sampling frequency is limited by the physical characteristics of the components: the pixel pitch, the rate of the analogtodigital (A/D) converter, etc. A lowpass filter is usually applied before the sampling operation to avoid aliasing. However, when multiple copies are ..."
Abstract

Cited by 18 (7 self)
 Add to MetaCart
In many applications, the sampling frequency is limited by the physical characteristics of the components: the pixel pitch, the rate of the analogtodigital (A/D) converter, etc. A lowpass filter is usually applied before the sampling operation to avoid aliasing. However, when multiple copies are available, it is possible to use the information that is inherently present in the aliasing to reconstruct a higher resolution signal. If the different copies have unknown relative offsets, this is a nonlinear problem in the offsets and the signal coefficients. They are not easily separable in the set of equations describing the superresolution problem. Thus, we perform joint registration and reconstruction from multiple unregistered sets of samples. We give a mathematical formulation for the problem when there are sets of samples of a signal that is described by expansion coefficients. We prove that the solution of the registration and reconstruction problem is generically unique