36772515
On the construction of systematic tEC/AUED codes
A new approach for the construction of systematic tEC/AUED codes is presented. These new constructions improve many values of the upper bound on the redundancy of the code for t=1 and 2. >
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.
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. >
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. >
17171833
What can be determined from a full and a weak perspective image?
This paper presents a first investigation on the structure from motion problem from the combination of full and weak perspective images. This problem arises in multiresolution object modeling where multiple zoomed-in or close-up views are combined with wider or distant reference views. The narrow field-of-view (FOV) images from the zoomed-in or closeup views can be approximated as weak perspective projection. Using a full perspective projection model for the narrow FOV images, although more accurate, actually leads to instabilities during the estimation process due to the non-linearities in the imaging model. The weak perspective approximation leads to more stable estimation algorithms, although at the cost of a small amount of modeling inaccuracy. Previous work in structure from motion focused either on two (or more) perspective images or on a set of weak perspective (more generally, affine) images. The main contribution of this paper is the study of the SFM problem for the much neglected case of one perspective and one (or more) weak perspective image. We show that in contrast to the case of a pair of weak perspective images, there is adequate information to recover Euclidean structure from a single perspective and a single weak perspective image. The epipolar geometry is simpler than with two perspective images leading to simpler and more stable estimation algorithms. Computer simulation shows that more stable results can be obtained with the technique presented in this paper than if two images are both considered to be full perspective.
45941410
The optimal service time allocation of a versatile server to queue jobs and stochastically available non-queue jobs of different types
Abstract In this paper, we consider a service system in which the server can process N + 1 different types of jobs. Jobs of type 0 are generated randomly according to a Poisson stream. Jobs of types 1 to N are non-queue types which may or may not be available for completion by the server. To optimally allocate the server's time to these jobs, we formulate a finite state semi-Markov decision process model to this environment. With this model, the optimal stationary policies can be numerically determined via a policy-iteration algorithm. We also discuss the practical applications of this model to tele-service and tele-marketing operations.
35739145
A Flexible Algorithm for Extracting Periodic Signals
In this paper, we propose a flexible two-stage algorithm for extracting desired periodic signals. In the first stage, if the period and phase information of the desired signal is available (or can be estimated), a minimum mean square error approach is used to coarsely recover the desired source signal. If only the period information is available (or can be estimated), a robust correlation based method is proposed to achieve the same goal. The second stage uses a higher-order statistics based Newton-like algorithm, derived from a constrained maximum likelihood criteria, to process the extracted noisy signal as cleanly as possible. A parameterized nonlinearity is adopted in this stage, adapted according to the estimated statistics of the desired signal. Compared with many existing extraction algorithms, the proposed algorithm has better performance, which is confirmed by simulations.
3159534
FAST: Toward more effective and efficient image retrieval
This paper focuses on developing a Fast And Semantics-Tailored (FAST) image retrieval methodology. Specifically, the contributions of FAST methodology to the CBIR literature include: (1) development of a new indexing method based on fuzzy logic to incorporate color, texture, and shape information into a region-based approach to improving the retrieval effectiveness and robustness; (2) development of a new hierarchical indexing structure and the corresponding hierarchical, elimination-based A* retrieval (HEAR) algorithm to significantly improve the retrieval efficiency without sacrificing the retrieval effectiveness; it is shown that HEAR is guaranteed to deliver a logarithm search in the average case; (3) employment of user relevance feedback to tailor the effective retrieval to each user's individualized query preference through the novel indexing tree pruning (ITP) and adaptive region weight updating (ARWU) algorithms. Theoretical analysis and experimental evaluations show that FAST methodology holds great promise in delivering fast and semantics-tailored image retrieval in CBIR.
12105004
New Measurements and Corner-Guidance for Curve Matching with Probabilistic Relaxation
Reliable curve matching is a difficult yet important problem in many vision-based applications including image-based modeling. We describe in this paper two aspects of our research in this area: a new algorithm for curve matching (including lines) within a probabilistic relaxation framework, and an approach of incorporating previously matched points/corners to guide curve matching. We propose similarity-invariant unary and binary measurements suitable for curves, and introduce an additional measurement to model the uncertainty of the binary measurements. The uncertainty measure is proven to be very important in computing the matching support from neighboring matches. We also show how to use a set of previously matched points/corners to guide the curve matching. The role of the corner guidance is explicitly modeled by a set of unary measurements and a similarity function under the same relaxation framework. Preprocessing techniques contributing to the success of our curve matching techniques are also developed and discussed. Experiments with complex real scenes show that the rate of correct matching is higher than 98%.