5523767
Closed Partition Lattice and Machine Decomposition
Finite-state machines are widely used to model systems in diverse areas. Often, the modeling machines can be decomposed into smaller component machines and this decomposition can facilitate the system design, implementation and analysis. J. Hartmanis and R.E. Stearns (1966) developed an elegant algebraic theory for machine decomposition that is based on the closed-partition lattice of a machine. In this paper, we study the computation of the closed-partition lattice of finite-state machines for the application to their decomposition. We present efficient algorithms for constructing the closed-partition lattice and for machine decomposition.
11856887
Approximation of linear functionals on a banach space with a Gaussian measure
Abstract We study approximation of linear functionals on separable Banach spaces equipped with a Gaussian measure. We study optimal information and optimal algorithms in average case, probabilistic, and asymptotic settings, for a general error criterion. We prove that adaptive information is not more powerful than nonadaptive information and that μ-spline algorithms, which are linear, are optimal in all three settings. Some of these results hold for approximation of linear operators. We specialize our results to the space of functions with continuous r th derivatives, equipped with a Wiener measure. In particular, we show that the natural splines of degree 2 r + I yield the optimal algorithms. We apply the general results to the problem of integration.
31110512
Discontinuity Detection and Thresholding-A Stochastic Approach
We study discontinuity detection and thresholding using a stochastic approach. We discuss a general form of detectors, which includes a number of well known detectors as special cases. Thresholding is indispensable to eliminate spurious responses from the detection process. We propose a Weighted Thresholding, which is designed to cope with a variety of anomalies. Our analysis and experimental results on real images show that intelligent thresholding methods can make a significant difference for discontinuity detection.
45853491
Testing Finite-State Machines: State Identification and Verification
We study the complexity of two fundamental problems in the testing of finite-state machines. 1) Distinguishing sequences (state identification). We show that it is PSPACE-complete to determine whether a finite-state machine has a preset distinguishing sequence. There are machines that have distinguishing sequences, but only of exponential length. We give a polynomial time algorithm that determines whether a finite-state machine has an adaptive distinguishing sequence. (The previous classical algorithms take exponential time.) Furthermore, if there is an adaptive distinguishing sequence, then we give an efficient algorithm that constructs such a sequence of length at most n(n/spl minus/1)/2 (which is the best possible), where n is the number of states. 2) Unique input output sequences (state verification). It is PSPACE-complete to determine whether a state of a machine has a unique input output sequence. There are machines whose states have unique input output sequences but only of exponential length. >
206418940
Residual Analysis for Feature Detection
It is shown that in a very simple form residual analysis achieves results that are at least as good as if not better than those obtained by other techniques. There are many ways for extensions of the method. For example, moving average filters of regularization can be used to obtain the residual images. Also, the strength of the correlation, measured by D/sub rr/(O), can be used to eliminate noise, weak edges, etc. A more ambitious extension is by considering smoothing filters that leave invariant the function representing the reflectance from smooth surfaces. >
38528864
Coping With Discontinuities In Computer Vision: Their Detection, Classification, And Measurement
40214240
Modeling automatic assembly and disassembly operations for virtual manufacturing
A system for evaluating products in their design phase has been developed for virtual manufacturing. It is integrated into a CAD/CAM environment to calculate the cost for assembling and disassembling parts. In our earlier work, a generic assembly and disassembly model was developed to represent operations required for product manufacturing and de-manufacturing. To be useful, the model requires a method for translating high-level instructions from product designers into low-level assembly and disassembly instructions. This paper presents a set of rules for accomplishing this task. The developed rules are used for manipulating strings representing parts and handlers in binary assembly and disassembly operations. A telephone assembly and disassembly simulation is used to illustrate the developed system.
15086505
A fast content-based indexing and retrieval technique by the shape information in large image database
Abstract In this paper, we present an efficient content-based image retrieval (CBIR) system which employs the shape information of images to facilitate the retrieval process. For efficient feature extraction, we extract the shape feature of images automatically using edge detection and wavelet transform which is widely used in digital signal processing and image compression. To facilitate speedy retrieval, we also propose the Spherical Pyramid-Technique (SPY-TEC), a new indexing method for similarity search in high-dimensional data space. The SPY-TEC is based on a special space partitioning strategy, which is to divide the d-dimensional data space first into 2d spherical pyramids, and then cut the single spherical pyramid into several spherical slices. This partition provides a transformation of d-dimensional space into 1-dimensional space. Thus, we are able to use a B+-tree to manage the transformed 1-dimensional data. We show that our image indexing method supports faster retrieval than other multi-dimensional indexing methods such as the R*-tree through various experiments. Finally, we show the retrieval effectiveness of our CBIR system using the measure proposed by the QBIC (C. Faloutsos et al., 1994) system.
10484740
Labeling Points on a Single Line
In this paper, we consider a map labeling problem where the points to be labeled are restricted on a line. It is known that the 1d-4P and the 1d-4S unit-square label placement problem and the Slope-4P unit-square label placement problem can both be solved in linear time and the Slope-4S unit-square label placement problem can be solved in quadratic time in Ref. [8]. We extend the result to the following label placement problem: Slope-4P fixed-height (width) label or elastic label placement problem and present a linear time algorithm for it provided that the input points are given sorted. We further show that if the points are not sorted, the label placement problems have a lower bound of Ω(n log n), where n is the input size, under the algebraic computation tree model. Optimization versions of these point labeling problems are also considered.
13592174
Critical area computation—a new approach
In this paper we present a new approach for computing the critical area for shorts in a circuit layout. The critical area calculation is the main computational problem in VLSI yield prediction. The method is based on the concept of Voronoi diagrams and computes the critical area for shorts (for all possible defect radii, assuming square defects) accurately in <italic>O</italic>(<italic>n</italic> log <italic>n</italic>) time, where <italic>n</italic> is the size of the input. The method is presented for rectilinear layouts but it is extendible to general layouts. As a byproduct we briefly sketch how to speed up the grid method of Wagner and Koren [16].
42364168
An Algorithm for Incremental Nearest Neighbor Search in High-Dimensional Data Spaces
The SPY-TEC (Spherical Pyramid-Technique) [8] was proposed as a new indexing method for high-dimensional data spaces using a special partitioning strategy that divides a d-dimensional data space into 2d spherical pyramids. Although the authors of [8] proposed an efficient algorithm for processing hyperspherical range queries, they did not propose an algorithm for processing k-nearest neighbor queries that are frequently used in similarity search. In this paper, we propose an efficient algorithm for processing exact nearest neighbor queries on the SPY-TEC by extending the incremental nearest neighbor algorithm proposed in [10]. We also introduce a metric that can be used to guide an ordered best-first traversal when finding nearest neighbors on the SPYTEC. Finally, we show that our technique significantly outperforms the related techniques in processing k-nearest neighbor queries by comparing it to the R*-tree, the X-tree, and the sequential scan through extensive experiments.