205118346
Coding for Write-Efficient Memory
We introduce write-efficient memories (WEM) as a new model for storing and updating information on a rewritable medium. There is a cost ϕ: X × X → R∞ assigned to changes of letters. A collection of subsets C = {Ci: 1 ≤ i ≤ M} of Xn is an (n, M, D) WEM code, if Ci ∩ Cj = ⊘ for all i ≠ j and if 
Dmax= maxl⩽i,j⩽MxnϵCjYnϵC1 max min ∑j=1nϕ(xt, yt)⩽D 
. Dmax is called the maximal correction cost with respect to the given cost function. The performance of a code C can also be measured by two parameters, namely, the maximal cost per letter dC = n−1Dmax and the rate of the size rC = n−1 log M. The rate achievable with a maximal per letter cost d is thus 
R(d)=supc:dc⩽drc 
. This is the most basic quantity (the storage capacity) of a WEM (Xn, ϕn)n = 1∞. We give a characterization of this and related quantities.
32960689
On Maximal Shadows of Members in Left-compressed Sets
Whereas Stanley, Proctor and others studied Sperner properties of the poset L(k,m) we consider shadows of left-compressed sets and derive asymptotic bounds on their sizes.
43476378
Partial converse for a relay channel
A special case of the general discrete memoryless relay channel is studied. This channel consists of an input x, a relay output z, a channel output y, and a noiseless channel of capacity C/sub r/ allowing the relay sender to send additional information to the decoder. The channel is described by a collection of distributions (p(y, z mod x)). The decoder uses the channel output y and a function f(z) of the relay output at a rate no greater than C/sub r/ to recover the message. Some results on the capacity of the channel are obtained. >
32850524
Linear inequalities for covering codes: Part I: Pair covering inequalities
The lower bounds on K(n,R), minimum number of codewords of any binary code of length n, and covering radius R are improved. A new technique combining the Hamming association scheme and the results of a classic problem of covering pairs by k-tuples is introduced. The new lower bounds are obtained by studying various linear inequalities satisfied by covering codes, and such an inequality is derived. The lower bounds for K(n,R) are studied for some special values of n and R, which serve as examples showing how the methods developed are applied to concrete cases. >
19004655
Identification via compressed data
A new coding problem is introduced for a correlated source (X/sup n/,Y/sup n/)/sub n=1//sup /spl infin//. The observer of X/sup n/ can transmit data depending on X/sup n/ at a prescribed rate R. Based on these data the observer of Y/sup n/ tries to identify whether for some distortion measure /spl rho/ (like the Hamming distance) n/sup -1/ /spl rho/(X/sup n/,Y/sup n/)/spl les/d, a prescribed fidelity criterion. We investigate as functions of R and d the exponents of two error probabilities, the probabilities for misacceptance, and the probabilities for misrejection. In the case where X/sup n/ and Y/sup n/ are independent, we completely characterize the achievable region for the rate R and the exponents of two error probabilities; in the case where X/sup n/ and Y/sup n/ are correlated, we get some interesting partial results for the achievable region. During the process, we develop a new method for proving converses, which is called "the inherently typical subset lemma". This new method goes considerably beyond the "entropy characterization" the "image size characterization," and its extensions. It is conceivable that this new method has a strong impact on multiuser information theory.
15006226
Bounds on the sizes of constant weight covering codes
Motivated by applications in universal data compression algorithms we study the problem of bounds on the sizes of constant weight covering codes. We are concerned with the minimal sizes of codes of lengthn and constant weightu such that every word of lengthn and weightv is within Hamming distanced from a codeword. In addition to a brief summary of part of the relevant literature, we also give new results on upper and lower bounds to these sizes. We pay particular attention to the asymptotic covering density of these codes. We include tables of the bounds on the sizes of these codes both for small values ofn and for the asymptotic behavior. A comparison with techniques for attaining bounds for packing codes is also given. Some new combinatorial questions are also arising from the techniques.
5858737
A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry
Abstract This paper proposes a robust approach to image matching by exploiting the only available geometric constraint, namely, the epipolar constraint. The images are uncalibrated, namely the motion between them and the camera parameters are not known. Thus, the images can be taken by different cameras or a single camera at different time instants. If we make an exhaustive search for the epipolar geometry, the complexity is prohibitively high. The idea underlying our approach is to use classical techniques (correlation and relaxation methods in our particular implementation) to find an initial set of matches, and then use a robust technique—the Least Median of Squares (LMedS)—to discard false matches in this set. The epipolar geometry can then be accurately estimated using a meaningful image criterion. More matches are eventually found, as in stereo matching, by using the recovered epipolar geometry. A large number of experiments have been carried out, and very good results have been obtained. Regarding the relaxation technique, we define a new measure of matching support, which allows a higher tolerance to deformation with respect to rigid transformations in the image plane and a smaller contribution for distant matches than for nearby ones. A new strategy for updating matches is developed, which only selects those matches having both high matching support and low matching ambiguity. The update strategy is different from the classical “winner-take-all”, which is easily stuck at a local minimum, and also from “loser-take-nothing”, which is usually very slow. The proposed algorithm has been widely tested and works remarkably well in a scene with many repetitive patterns.
9407873
Linear combination representation for outlier detection in motion tracking
In this paper we show that Ullman and Basri's linear combination (LC) representation, which was originally proposed for alignment-based object recognition, can be used for outlier detection in motion tracking with an affine camera. For this task LC can be realized either on image frames or feature trajectories, and therefore two methods are developed which we call linear combination of frames and linear combination of trajectories. For robust estimation of the linear combination coefficients, the support vector regression (SVR) algorithm is used and compared with the RANSAC method. SVR based on quadratic programming optimization can efficiently deal with more than 50 percent outliers and delivers more consistent results than RANSAC in our experiments. The linear combination representation can use SVR in a straightforward manner while previous factorization-based or subspace separation methods cannot. Experimental results are presented using real video sequences to demonstrate the effectiveness of our LC+SVR approaches, including a quantitative comparison of SVR and RANSAC.
1727845
Estimating the Fundamental Matrix by Transforming Image Points in Projective Space
This paper proposes a novel technique for estimating the fundamental matrix by transforming the image points in projective space. We therefore only need to perform nonlinear optimization with one parameterization of the fundamental matrix, rather than considering 36 distinct parameterizations as in previous work. We also show how to preserve the characteristics of the data noise model from the original image space.
5688571
Enhancing Downlink Performance in Wireless Networks by Simultaneous Multiple Packet Transmission
In this paper, we consider using simultaneous Multiple Packet Transmission (MPT) to improve the downlink performance of wireless networks. With MPT, the sender can send two compatible packets simultaneously to two distinct receivers and can double the throughput in the ideal case. We formalize the problem of finding a schedule to send out buffered packets in minimum time as finding a maximum matching problem in a graph. Since maximum matching algorithms are relatively complex and may not meet the timing requirements of real-time applications, we give a fast approximation algorithm that is capable of finding a matching at least 3/4 of the size of a maximum matching in O(|E|) time, where |E| is the number of edges in the graph. We also give analytical bounds for maximum allowable arrival rate, which measures the speedup of the downlink after enhanced with MPT, and our results show that the maximum arrival rate increases significantly even with a very small compatibility probability. We also use an approximate analytical model and simulations to study the average packet delay, and our results show that packet delay can be greatly reduced even with a very small compatibility probability.
9741831
A performance model for fine-grain accesses in UPC
UPC's implicit communication and fine-grain programming style make application performance modeling a challenging task. The correspondence between remote references and communication events depends on the internals of the compiler and runtime system. This correspondence is often hidden from application developers. Aggressive optimizations allowed by the relaxed memory consistency model further blur this correspondence by transforming code structure. A modeling approach based on UPC platform benchmarking and code analysis is proposed. This approach abstracts a UPC platform according to its potential to apply a few common optimizations, then divides remote references in the application code into groups, based on a dependence analysis, that are amenable to each optimization. Each group is associated with a cost, obtained via benchmarking each potential optimization. The aggregated cost of these groups is the predicted cost of the application. Three simple UPC applications modeled using this approach usually yielded performance predictions within 15 percent of actual running times