The DS-CDMA signal model and the noisy linear independent component analysis (ICA) model are analyzed in this paper. Comparing these models shows that they have the same form. The adaptive minimum mean-square error (M...
The DS-CDMA signal model and the noisy linear independent component analysis (ICA) model are analyzed in this paper. Comparing these models shows that they have the same form. The adaptive minimum mean-square error (MMSE) multiuse detection based on ICA is proposed. It uses the output of adaptive MMSE multi-user detection to initialize the ICA iterations, not only the known spread information of interesting user is used to overcome the uncertainness of ICA, but also the character of statistical independence is used. The simulation results show that the performance is improved obviously.
Engineering optimization in the intelligence swarm remains to be a challenge. Recently, a novel optimization method based on number-theory and particle swarm, good lattice swarm optimization algorithm(GLSO), is introd...
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Engineering optimization in the intelligence swarm remains to be a challenge. Recently, a novel optimization method based on number-theory and particle swarm, good lattice swarm optimization algorithm(GLSO), is introduced, which intends to produce faster and better global search ability and more accurate convergence because it has a solid theoretical basis. In this paper, four models of constructing good point set are introduced and the GLSO based on new models is rewritten. Some applications of the new model on constrained engineering via employing a penalty function approach suggest that the presented algorithm is potentially a powerful search technique for solving complex engineering design optimization problems.
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.
In this article, we propose a (t,n) threshold verifiable multi-secret sharing scheme, in which to reconstruct t secrets needs to solve t simultaneous equations. The analysis results show that our scheme is as easy as ...
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In this article, we propose a (t,n) threshold verifiable multi-secret sharing scheme, in which to reconstruct t secrets needs to solve t simultaneous equations. The analysis results show that our scheme is as easy as Yang's scheme [8] in the secret reconstruction and requires less public values than Chien's [7] and Yang's schemes. Furthermore, the shares in our scheme can be verified their validity with t public values based on ECDLP, and there are two verified forms: one is computationally secure as Feldman 's scheme [12] and other is unconditionally secure as Pedersen's scheme [13]. In addition, for the main computation: a i,1 P 1 + a i,2 P 2 + hellip + a i,t P t in our scheme, we present a new method based on the signed factorial expansion and implement it, the results show that it is more efficient than the current public methods. Thus our scheme is a secure and efficient (t,n) threshold verified multi-secret sharing scheme.
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.
A novel image content authentication algorithm based on Laplace spectra was proposed. Outstanding feature points are extracted from the original image and a cipher point is inserted. A relational graph is then built, ...
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ISBN:
(纸本)7900719229
A novel image content authentication algorithm based on Laplace spectra was proposed. Outstanding feature points are extracted from the original image and a cipher point is inserted. A relational graph is then built, and the Laplace spectra of the graph are calculated to serve as image features. The Laplace spectra are quantized then embedded into the original image as a watermark. In the authentication step, the Laplace spectra of the authenticating image are calculated and compared with that of the watermark embedded in the authenticating image. If both of the spectra are identical, the image passes the authentication test. Otherwise, the tamper is found. The experimental results show that the proposed authentication algorithm can effectively detect the event and the location when the original image content is tampered viciously.
Concept hierarchies are important in many generalized data mining applications, such as multiple-level fuzzy association rule mining. Usually concept hierarchies are given by domain experts. However, it is extremely d...
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Concept hierarchies are important in many generalized data mining applications, such as multiple-level fuzzy association rule mining. Usually concept hierarchies are given by domain experts. However, it is extremely difficult and time-consuming for human experts to discover concepts and construct concept hierarchies from the domain. In literature, several representations of concept hierarchy are possible, for example tree, lattice, table, linked list, arbitrary graph etc. In this paper, we apply quotient space model to representing concept hierarchies. In contrast to others, the representation model is much more extensible and compatible. The results indicate that this technique can improve the efficiency of performing the generalization and specialization operation in concept hierarchies.
Using symplectic integrator propagator, a three-dimensional fourth-order symplectic finite difference time domain (SFDTD) method is studied, which is of the fourth order in both the time and space domains. The metho...
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Using symplectic integrator propagator, a three-dimensional fourth-order symplectic finite difference time domain (SFDTD) method is studied, which is of the fourth order in both the time and space domains. The method is nondissipative and can save more memory compared with the traditional FDTD method. The total field and scattered field (TF-SF) technique is derived for the SFDTD method to provide the incident wave source conditions. The bistatic radar cross section (RCS) of a dielectric sphere is computed by using the SFDTD method for the first time. Numerical results suggest that the SFDTD algorithm acquires better stability and accuracy compared with the traditional FDTD method.
In tile process of the reconstruction of digital holography. the traditional methods of diffraction and filtration are commonly adopted to recover the original complex-wave signal. Influenced by twin-image and zero-or...
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In tile process of the reconstruction of digital holography. the traditional methods of diffraction and filtration are commonly adopted to recover the original complex-wave signal. Influenced by twin-image and zero-order terms, the above-mentioned methods, however, either limit tile field of vision or result in the loss of the amplitude and phase. A new method for complex-wave retrieval is presented, which is based on blind signal separation. Three frames of holograms are captured by a charge coupled device (CCD) camera to form an observation signal. The term containing only amplitude and phase of complex-wave is separated, by means of independent component analysis, from the observation signal, which effectively eliminates the zero-order term. Finally. the complex-wave retrieval of pure phase wavefront is achieved. Experimental results show that this method can better recover the amplitude and phase of the original complex-wave even when there is a frequency spectrum mixture in the hologram.
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