This paper is to predict economic development based on wavelet least squares support vector machine algorithm. The same as support vector machine, least squares support vector machine employs the principle of structur...
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Video summarization provides condensed and succinct representations of the content of a video stream. A static storyboard summarization approach based on robust low-rank subspace segmentation is proposed in this paper...
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Due to the semantic gap between low-level visual feature and high-level semantic concept, image annotation plays an important role in image retrieval. In this paper, an automatic image annotation approach using semant...
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A whisper intelligibility enhancement method was proposed based on the Real-valued Discrete Gabor Transform (RDGT) in the joint time frequency domain where the RDGT can change the density of the spectrum through the o...
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Membrane algorithms are a new class of heuristic algorithms, which attempt to incorporate some components of membrane computing models (also called P systems) for designing efficient optimization algorithms, such as t...
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Membrane algorithms are a new class of heuristic algorithms, which attempt to incorporate some components of membrane computing models (also called P systems) for designing efficient optimization algorithms, such as the structure of P systems, the way of communication between cells, etc. Membrane algorithms are a kind of parallel methods, where many operations can be performed in parallel. Although the importance of the parallelism of such algorithms is recognized, membrane algorithms were often implemented on the serial computing device Central processing Unit (CPU), which makes the algorithms cannot work in a more efficient way. In this work, we consider the implementation of membrane algorithms on the parallel computing device Graphics processing Unit (GPU). Under such implementation, all cells of membrane algorithms can work simultaneously. Experiment results on two classical intractable problems, point set matching problem and TSP, show that GPU implementation of membrane algorithms is much more efficient than CPU implementation in terms of runtime, especially for solving the problems with a high complexity.
Increasing number of research activities and different types of studies in brain-computer interface systems (BCIs) show potential in this young research area. However, BCIs have not become widely applied, most of them...
Increasing number of research activities and different types of studies in brain-computer interface systems (BCIs) show potential in this young research area. However, BCIs have not become widely applied, most of them are still limited in the laboratory and off-line. One of the important reasons is that: EEG signal acquisition is completed by the professional medical equipments. They are expensive and the parameters of them cannot be flexiblely changed with the specific BCI experiment paradigm. In the paper, a single-channel low-cost circuit of EEG signal acquisition for the BCI system is designed. The circuit is composed of protection circuit, instrumentation amplifier, common mode rejection (CMR) circuit, gain adjustable amplifiers and filters. In order to test this circuit, the circuit simulation and the real-time EEG measurements are implemented. The experimental results show that the circuit is effective with good performance, it is very suitable for the online BCI system.
This letter presents the graphic processor unit (GPU)implementation of the finite-difference time-domain (FDTD)method for the solution of the two-dimensional electromagnetic fields inside dispersive *** improved Z-tra...
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This letter presents the graphic processor unit (GPU)implementation of the finite-difference time-domain (FDTD)method for the solution of the two-dimensional electromagnetic fields inside dispersive *** improved Z-transform-based finite-difference time-domain (ZTFDTD) method was presented for simulating the interaction of electromagnetic wave with unmagnetized *** using the newly introduced Compute Unified Device Architecture (CUDA) technology, we illustrate the efficacy of GPU in accelerating the FDTD computations by achieving significant speedups with great ease and at no extra hardware *** effect of the GPU-CPU memory transfers on the speedup will be also studied.
In this paper, we propose a novel model of three points named TP for location estimation in wireless sensor networks (WSNs) with random deployment of anchor nodes. In this model, we select three anchor nodes which hav...
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In this paper, we develop a novel fuzzy supervised learning algorithm based on the dynamical parameter estimation. First, a reformative supervised fuzzy LDA algorithm (RF-LDA) for the training samples is proposed. Com...
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In the real word, the complex problems usually have netted structure, namely netted problems. The general methods to solve this kind of problems are based on the sequence structural description or tree structural desc...
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