A novel Pareto-based multi-objective fully-informed particle swarm algorithm (FIPS) is proposed to solve flexible job-shop problems in this paper. Firstly, the population is ranked based on Pareto optimal concept. And...
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A novel Pareto-based multi-objective fully-informed particle swarm algorithm (FIPS) is proposed to solve flexible job-shop problems in this paper. Firstly, the population is ranked based on Pareto optimal concept. And the neighborhood topology used in FIPS is based on the Pareto rank. Secondly, the crowding distance of individuals is computed in the same Pareto level for the secondary rank. Thirdly, addressing the problem of trapping into the local optimal, the mutation operators based on the coding mechanism are introduced into our algorithm. Finally, the performance of the proposed algorithm is demonstrated by applying it to several benchmark instances and comparing the experimental results.
The mechanism of the classical particle swarm optimization and the comparison criterion of different natural computing methods is investigated by introducing the discrepancy and good lattice points in number theory an...
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The mechanism of the classical particle swarm optimization and the comparison criterion of different natural computing methods is investigated by introducing the discrepancy and good lattice points in number theory and proposes a novel optimization method, called good lattice points-based particle swarm optimization algorithm, which intends to produce faster and more accurate convergence because it has a solid theoretical basis and better global search ability, meanwhile the global convergence of the presented algorithm with asymptotic probability one is proved by the property of the optimal lattice. Finally experiment results are very promising to illustrate the outstanding feature of the presented algorithm.
Wavelet coding has been shown to be better than discrete cosine transform (DCT) in image/video processing. Moreover, it has the feature of scalability, which is involved in modern video standards. This work presents n...
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ISBN:
(纸本)9780769530581;0769530583
Wavelet coding has been shown to be better than discrete cosine transform (DCT) in image/video processing. Moreover, it has the feature of scalability, which is involved in modern video standards. This work presents novel algorithms, namely 2-D symmetric mask-based discrete wavelet transform (SMDWT), to improve the critical issue of the 2-D lifting-based discrete wavelet transform (LDWT), and then obtains the benefit of low latency, high-speed operation, and low temporal memory. The SMDWT also has the advantages of high-performance embedded periodic extension boundary treatment, reduced complexity, regular signal coding, short critical path, reduced latency time, and independent subband coding processing. Moreover, the 2-D lifting-based DWT performance can also be easily improved by exploiting appropriate parallel method inherently in SMDWT. Comparing with the normal 2-D 5/3 integer lifting-based DWT the proposed method significantly improves lifting-based latency and complexity in 2-D DWT without degradation in image quality. The algorithm can be applied to real-time image/video applications, such as JPEG2000, MPEG-4 still texture object decoding, and wavelet-based Scalable Video Coding (SVC).
This study proposes a speech recognition method which is made robust to noise by combining speech signal estimation based on GMM and speech enhancement based on SVD in the temporal domain. Conventional speech signal e...
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The matrix inversion lemma gives an explicit formula of the inverse of a positive-definite matrix A added to a block of dyads (represented as BBH) as follows: (A + BB H ) -1 = A -1 - A -1 B(I + B H A -1 B) -1 B...
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The matrix inversion lemma gives an explicit formula of the inverse of a positive-definite matrix A added to a block of dyads (represented as BBH) as follows: (A + BB H ) -1 = A -1 - A -1 B(I + B H A -1 B) -1 B H A -1 . It is well-known in the literature that this formula is very useful to develop a block-based recursive least-squares algorithm for the block-based recursive identification of linear systems or the design of adaptive filters. We extend this result to the case when the matrix A is singular, and present a matrix pseudo-inversion lemma. Based on this result, we propose a block-based adaptive multi-channel super-exponential algorithm (BAMSEA). We present simulation results for the performance of the block-based algorithm in order to show the usefulness of the matrix pseudo-inversion lemma.
A novel, computationally efficient and robust scheme for multiple initial point prediction has been proposed in this paper. A combination of spatial and temporal predictors has been used for initial motion vector pred...
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A novel, computationally efficient and robust scheme for multiple initial point prediction has been proposed in this paper. A combination of spatial and temporal predictors has been used for initial motion vector prediction, determination of magnitude and direction of motion and search pattern selection. Initially three predictors from the spatio-temporal neighbouring blocks are selected. If all these predictors point to the same quadrant then a simple search pattern based on the direction and magnitude of the final predicted motion vector is selected. However if the predictors belong to different quadrants then we start the search from multiple initial points to get a clear idea of the location of minimum point. In this case a small rood search pattern has been selected. The predictive search center is closer to the global minimum and thus decreases the effect of monotonic error surface assumption and its impact on the motion field. Its additional advantage is that it moves the search closer to the global minimum hence increases the computation speed. Further computational speed up has been obtained by considering the zero motion threshold for no motion blocks, and, specialized rood search pattern. The image quality measured in terms of PSNR also shows good results.
An algorithm of improved reduced spatial resolution video transcoding is proposed in this paper. An adaptive intra-refresh scheme is presented based on the relation between drift error and motion activity of inter-cod...
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An algorithm of improved reduced spatial resolution video transcoding is proposed in this paper. An adaptive intra-refresh scheme is presented based on the relation between drift error and motion activity of inter-coded blocks. The thresholds are dynamically adjusted according to the difference between the target bit rate and actual bit rate. This method can reduce the bit rate of intra coded frames while still maintaining error robustness and limiting temporal propagation of errors. Besides, a linear rate control strategy is also present. In order to reduce computational complexity, the rate-distortion function can be mapped into a linear function. The simulation results show that the buffer fullness tend to be stabilized and the PSNR of the reconstructed image is raised.
Automatic keyword extraction is one of the most important techniques in natural language processing. In this paper, features of complex networks composed of Chinese are studied. A novel automatic keyword extraction al...
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Automatic keyword extraction is one of the most important techniques in natural language processing. In this paper, features of complex networks composed of Chinese are studied. A novel automatic keyword extraction algorithm for Chinese document is proposed which is based on the features of the complex networks according to the small world structure in language networks and the theoretical achievements in complex networks. It extracts keyword based on the feature values of the word nodes in a documental language network. Experimental results show the proposed algorithm obtains higher average precision compared with the keyword extraction algorithm based on TFIDF.
It has been shown that CMOS imaging technology can be applied to Digital Autoradiography (AR) as a potential imaging alternative technology to using conventional film emulsion. In this work a thorough investigation on...
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It has been shown that CMOS imaging technology can be applied to Digital Autoradiography (AR) as a potential imaging alternative technology to using conventional film emulsion. In this work a thorough investigation on the performance of CMOS technology used in AR is presented. 3{sup left}H is a particularly important radioisotope used in AR because it can label many sites on biomolecules and provides the highest resolution images due to its low energy and hence low particle range compared to other beta-emitting radioisotopes. In order to detect β-particles from 3{sup left}H beta decay a back-thinned CMOS sensor has been used. Back-thinning is a standard process in CCDs but it is not widely applied to CMOS sensors. In this paper the first results of imaging a calibrated 3{sup left}H microscale and the first tritiated autoradiogram obtained with a back-thinned CMOS sensor at room temperature are presented.
While conventional approaches of BCI feature extraction are based on the power spectrum, we have tried using nonlinear features for classifying BCI data. In this paper, we report our test results and findings, which i...
While conventional approaches of BCI feature extraction are based on the power spectrum, we have tried using nonlinear features for classifying BCI data. In this paper, we report our test results and findings, which indicate that the proposed method is a potentially useful addition to current feature extraction techniques.
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