Study on approximation capabilities of fuzzy systems has been an important and hot issue for many years. Many existing studies on fuzzy systems based on standard affine TS fuzzy models suffer seriously from curse of d...
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Multiword Expressions (MWEs) appear frequently and ungrammatically in the natural languages. Identifying MWEs in free texts is a very challenging problem. This paper proposes a knowledge-free, training-free, and langu...
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Multiword Expressions (MWEs) appear frequently and ungrammatically in the natural languages. Identifying MWEs in free texts is a very challenging problem. This paper proposes a knowledge-free, training-free, and language-independent Multiword Expression Distance (MED). The new metric is derived from an accepted physical principle, measures the distance from an n-gram to its semantics, and outperforms other state-of-the-art methods on MWEs in two applications: question answering and named entity extraction.
Hysteretic optimization (HO) is a recently proposed optimization method based on the well-known demagnetization process of magnetic materials in physics. In this study, we apply HO to the protein folding problem, an a...
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Hysteretic optimization (HO) is a recently proposed optimization method based on the well-known demagnetization process of magnetic materials in physics. In this study, we apply HO to the protein folding problem, an attractive problem in computational biology, by generalizing the external field. The experimental results with benchmark problems show the proposed method is competitive with other popular algorithms, such as extremal optimization.
Much of the previous work in the protein field focused on the 2D protein folding due to its simplicity but ignored the 3D protein folding problem. In this paper, based on the work of 2D protein folding problem by prim...
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Much of the previous work in the protein field focused on the 2D protein folding due to its simplicity but ignored the 3D protein folding problem. In this paper, based on the work of 2D protein folding problem by primary extremal optimization (EO) algorithm, we study the more complicated 3D protein folding problem with its variation (τ-EO) for the first time. The parameter τ is set as a random value near a constant in each iteration. For the protein with not too long sequence, the experimental results show that the proposed EO algorithm is very efficient.
In this paper, a new type of autonomous vehicle is developed. This vehicle consists of three sets of control systems to regulate the direction, brake and fuels. The sensing system is a combination of laser radar and c...
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In this paper, a new type of autonomous vehicle is developed. This vehicle consists of three sets of control systems to regulate the direction, brake and fuels. The sensing system is a combination of laser radar and camera. The localization system is constructed with GPS device and electronically compass. Currently, three tasks, including lane detection and following, object detection, and obstacle avoidance, has been implemented on this platform. We reported some experimental results.
The combinatorial optimization occurs in many real-world problems including the fields of engineering, physics and economics. It has been recognized that some problems with highly degenerate states are difficult to so...
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The combinatorial optimization occurs in many real-world problems including the fields of engineering, physics and economics. It has been recognized that some problems with highly degenerate states are difficult to solve in terms of many existing optimization algorithms. This paper proposes a novel stochastic method with modified extremal optimization (EO) and nearest neighbor search to deal with these problems. It starts from making use of the recent discovered statistical property to generate the initial configurations by the nearest neighbor search and then further explores the complex configuration spaces by a modified EO approach that applies more general probability distributions-based evolution mechanism. The experimental results with some hard instances of traveling salesman problem (TSP), a popular benchmark for combinatorial optimization problems demonstrate that the proposed method may provide better performance than other physics-inspired algorithms such as simulated annealing, EO and self-organized algorithm.
In this paper, a discriminated correlation classifier is proposed to improve the performance of the two-dimensional (2-D) face recognition algorithm. Until now, many methods have been proposed to address the problems ...
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In crowding, neighboring distractors impair the visual perception of a presented ta get. We study influences by the configuration of distractors on the bias to perceive the orientation of a target. Our results show th...
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ISBN:
(纸本)9781424451814;9781424451821
In crowding, neighboring distractors impair the visual perception of a presented ta get. We study influences by the configuration of distractors on the bias to perceive the orientation of a target. Our results show that: (a) when distractors are similar to each other but different from target, crowding is decreased;(b) when distractors form a subjective contour, crowding is also reduced. These results illustrate that crowding is weak whenever the target stands out from the context and strong when the target is grouped into the context as a part of a global percept. In addition, we show how a Bayesian model, based on the principle of spatial resolution of attention that is modulated by the large size of receptive fields, can account for the behavioral data.
In this paper, an adaptive spectral doppler estimation based on recursive least squares (RLS) algorithm is proposed for blood velocity distribution estimation. The purpose is to (i) minimize the observation window nee...
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A bipartite state, which is secretly chosen from a finite set of known entangled pure states, cannot immediately be useful in standard quantum information processing tasks. To effectively make use of the entanglement ...
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A bipartite state, which is secretly chosen from a finite set of known entangled pure states, cannot immediately be useful in standard quantum information processing tasks. To effectively make use of the entanglement contained in this unknown state, we introduce a way to locally manipulate the original quantum system: either identify the state successfully or distill some pure entanglement. Remarkably, if many copies are available, we show that any finite set of entangled pure states, whether orthogonal or not, can be locally distinguished in this way, which further implies that pure entanglement can be deterministically extracted from unknown entanglement. These results make it clear why a large class of entangled bipartite quantum operations including unitary operations and measurements that are globally distinguishable can also be locally distinguishable: They can generate pure entanglement consistently.
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