Image filtering is fundamental in image processing. The acceleration is essential since image resolution has highly increased. For the acceleration, image subsampling is a general approach for any filtering. However, ...
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ISBN:
(纸本)9781538662496
Image filtering is fundamental in image processing. The acceleration is essential since image resolution has highly increased. For the acceleration, image subsampling is a general approach for any filtering. However, this approach has a drawback in accuracy due to image aliasing. Several papers moderate this problem by subsampling image or filtering kernel non-sequential sampling. In this paper, we improve the sampling combined with image and kernel subsampling. We also accelerate the work of non-sequential sampling by vector addressing of hardware acceleration. Experimental results show that the proposed method accelerate bilateral filtering and adaptive Gaussian filtering. Also, the proposed vector addressing accelerate both filters.
Given n sensors and m targets, a monitoring schedule is a partition of the sensor set such that each part of the partition can monitor all targets. Monitoring schedules are used to maximize the time all targets are mo...
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ISBN:
(纸本)9780769549309
Given n sensors and m targets, a monitoring schedule is a partition of the sensor set such that each part of the partition can monitor all targets. Monitoring schedules are used to maximize the time all targets are monitored when there is no possibility of replacing the batteries of the sensors. Each part of the partition is used for one unit of time, and thus the goal is to maximize the number of parts in the partition. We present distributed algorithms for Monitoring Schedule under the following assumptions: 1) identical sensors can each monitor all targets within a certain radius, 2) the n sensors are randomly distributed uniformly in a large square containing the targets, 3) the number of sensors is high enough given the area the square, and 4) the communication range is at least a constant times the the sensing range. We present randomized distributed algorithms that achieve a constant factor approximation in polylogarithmic number of communication rounds, with high probability. These results hold if we make one of the following two assumptions: 1) any two sensors within communication range are able to estimate within a constant their relative distance, or 2) the communication range is an exact fraction of the sensing range. We improve the results of Calinescu and Ellis (DIAL M-POMC '08) by eliminating the assumption that the communication range must be twice the sensing range, and by this result holding with fewer sensors.
This paper proposes a recognition model for English handwritten (lowercase, uppercase and letter) character recognition that uses Freeman chain code (FCC) as the representation technique of an image character. Chain c...
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ISBN:
(纸本)9780769539829
This paper proposes a recognition model for English handwritten (lowercase, uppercase and letter) character recognition that uses Freeman chain code (FCC) as the representation technique of an image character. Chain code representation gives the boundary of a character image in which the codes represent the direction of where is the location of the next pixel. An FCC method that uses 8-neighbourhood that starts from direction labelled as 1 to 8 is used. randomized algorithm is used to generate the FCC. After that, features vector is built. The criteria of features to input the classification is the chain code that converted to 64 features. Support vector machine (SVM) is chosen for the classification step. NIST Databases are used as the data in the experiment. Our test results show that by applying the proposed model, we reached a relatively high accuracy for the problem of English handwritten recognition.
For an even integer t >= 2, the Matching Connectivity matrix H-t is a matrix that has rows and columns both labeled by all perfect matchings of the complete graph K-t on t vertices;an entry H-t[M-1, M-2] is 1 if M-...
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ISBN:
(纸本)9781450320290
For an even integer t >= 2, the Matching Connectivity matrix H-t is a matrix that has rows and columns both labeled by all perfect matchings of the complete graph K-t on t vertices;an entry H-t[M-1, M-2] is 1 if M-1 U M-2 is a Hamiltonian cycle and 0 otherwise. Motivated by the computational study of the Hamiltonicity problem, we present three results on the structure of H-t: We first show that H-t has rank exactly 2(t/2-1) over GF(2) via an appropriate factorization that explicitly provides families of matchings X-t forming bases for H-t. Second, we show how to quickly change representation between such bases. Third, we notice that the sets of matchings X-t induce permutation matrices within H-t. We use the factorization to derive an 1.888(n) n(O(1)) time Monte Carlo algorithm that solves the Hamiltonicity problem in directed bipartite graphs. Our algorithm as well counts the number of Hamiltonian cycles modulo two in directed bipartite or undirected graphs in the same time bound. Moreover, we use the fast basis change algorithm from the second result to present a Monte Carlo algorithm that given an undirected graph on n vertices along with a path decomposition of width at most pw decides Hamiltonicity in (2 + root 2)P(w)n(O(1)) time. Finally, we use the third result to show that for every epsilon > 0 this cannot be improved to (2 + root 2 - epsilon)P-w n(O(1)) time unless the Strong Exponential Time Hypothesis fails, i.e., a faster algorithm for this problem would imply the breakthrough result of an O((2 - epsilon ')(n)) time algorithm for CNF-Sat.
For any T >= 1, there are constants R = R(T) > 1 and zeta = zeta((T) > 0 and a randomized algorithm that takes as input an integer n and two strings x, y of length at most n, and runs in time O(n(1+1/T)) and ...
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ISBN:
(纸本)9781450369794
For any T >= 1, there are constants R = R(T) > 1 and zeta = zeta((T) > 0 and a randomized algorithm that takes as input an integer n and two strings x, y of length at most n, and runs in time O(n(1+1/T)) and outputs an upper bound U on the edit distance of d(edit)(x, y) that with high probability, satisfies U <= R(d(edit)(x, y) + n(1-zeta)). particular, on any input with d(edit)(x, y) >= n(1-zeta) the algorithm outputs a constant factor approximation with high probability. A similar result has been proven independently by Brakensiek and Rubinstein (this proceedings).
Let G be a directed edge-weighted graph and let P be a shortest path from s to t in G. The replacement paths problem asks to compute, for every edge e on P, the shortest s-to-t path that avoids e. Apart from approxima...
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ISBN:
(纸本)9780769542447
Let G be a directed edge-weighted graph and let P be a shortest path from s to t in G. The replacement paths problem asks to compute, for every edge e on P, the shortest s-to-t path that avoids e. Apart from approximation algorithms and algorithms for special graph classes, the naive solution to this problem removing each edge e on P one at a time and computing the shortest s-to-t path each time - is surprisingly the only known solution for directed weighted graphs, even when the weights are integrals. In particular, although the related shortest paths problem has benefited from fast matrix multiplication, the replacement paths problem has not, and still required cubic time. For an n-vertex graph with integral edge-lengths between -M and M, we give a randomized algorithm that uses fast matrix multiplication and is sub-cubic for appropriate values of M. We also show how to construct a distance sensitivity oracle in the same time bounds. A query (u,v,e) to this oracle requires sub-quadratic time and returns the length of the shortest u-to-v path that avoids the edge e. In fact, for any constant number of edge failures, we construct a data structure in sub-cubic time, that answer queries in sub-quadratic time. Our results also apply for avoiding vertices rather than edges.
We propose a novel kernel-level memory allocator, called M-3 (M-cube, Multi-core Multi-bank Memory allocator), that has the following two features. First, it introduces and makes use of a notion of a memory container,...
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ISBN:
(纸本)9781450318709
We propose a novel kernel-level memory allocator, called M-3 (M-cube, Multi-core Multi-bank Memory allocator), that has the following two features. First, it introduces and makes use of a notion of a memory container, which is defined as a unit of memory that comprises the minimum number of page frames that can cover all the banks of the memory organization, by exclusively assigning a container to a core so that each core achieves bank parallelism as much as possible. Second, it orchestrates page frame allocation so that pages that threads access are dispersed randomly across multiple banks so that each thread's access pattern is randomized. The development of M-3 is based on a tool that we develop to fully understand the architectural characteristics of the underlying memory organization. Using an extension of this tool, we observe that the same application that accesses pages in a random manner outperforms one that accesses pages in a regular pattern such as sequential or same ordered accesses. This is because such randomized accesses reduces inter-thread access interference on the rowbuffer in memory banks. We implement M-3 in the Linux kernel version 2.6.32 on the Intel Xeon system that has 16 cores and 32GB DRAM. Performance evaluation with various workloads show that M-3 improves the overall performance for memory intensive benchmarks by up to 85% with an average of about 40%.
The Quadratic Assignment Problem(QAP) is one of the hardest combinatorial optimization problems known. Ant algorithms have been inspired by the behavior of real ant colonies. In this paper, we introduce random algorit...
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ISBN:
(纸本)9780769530062
The Quadratic Assignment Problem(QAP) is one of the hardest combinatorial optimization problems known. Ant algorithms have been inspired by the behavior of real ant colonies. In this paper, we introduce random algorithm to the constructive procedure of the solution of Ant System (AS) and adopt dynamic adaptive approach to update pheromone trails. In our algorithm, only partial facilities are randomly chosen to compute the designed probability. Experimental results for solving the QAP demonstrate that the proposed approach can obtain the better quality of the solutions.
This paper proposes a probabilistic robust control approach for a small unmanned aerial vehicle(UAV) in longitudinal ight. In the proposed method, the stochastic behavior of uncertainty parameters is considered in sol...
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ISBN:
(纸本)9781509009107
This paper proposes a probabilistic robust control approach for a small unmanned aerial vehicle(UAV) in longitudinal ight. In the proposed method, the stochastic behavior of uncertainty parameters is considered in solving a high-performance robust controller of UAV. Compared to deterministic robust control, this solution has two advantages:(a) the controller obtained by the proposed method has xed order;(b) it is less-conservative and more reasonable for controlling ight control systems with bounded uncertainty. Simulation results for an UAV in longitudinal motion are given to show the effectiveness of the proposed approach.
We describe a unified framework for random interpretation that generalizes previous randomized intraprocedural analyses, and also extends naturally to efficient interprocedural analyses. There is no such natural exten...
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We describe a unified framework for random interpretation that generalizes previous randomized intraprocedural analyses, and also extends naturally to efficient interprocedural analyses. There is no such natural extension known for deterministic algorithms. We present a general technique for extending any intraprocedural random interpreter to perform a context-sensitive interprocedural analysis with only polynomial increase in running time. This technique involves computing random summaries of procedures, which are complete and probabilistically sound. As an instantiation of this general technique, we obtain the first polynomial-time randomized algorithm that discovers all linear relationships interprocedurally in a linear program. We also obtain the first polynomial-time randomized algorithm for precise interprocedural value numbering over a program with unary uninterpreted functions. We present experimental evidence that quantifies the precision and relative speed of the analysis for discovering linear relationships along two dimensions: intraprocedural vs. interprocedural, and deterministic vs. randomized. We also present results that show the variation of the error probability in the randomized analysis with changes in algorithm parameters. These results suggest that the error probability is much lower than the existing conservative theoretical bounds.
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