Advanced Materials Research Vols. 926-930

Abstract: The spectrum estimation is a main content of modern signal processing, it is very important for random signal detection and analysis. This paper researched the classical spectrum estimation method, simulated the periodogram method, Barlett method, and Welch method of power spectrum estimation, then mainly discussed the spectral resolution about different length of data, also discussed the resolution of the spectral estimation and the performance of variance in the different way.

Abstract: In this paper, the concept of (G) fuzzy integral on a fuzzy set is given and the basic properties of it are discussed. Monotone Convergence Theorem and Fatou Lemma are proved. Finally, A necessary and sufficient condition on which (G) fuzzy integrals of two fuzzy measurable functions on fuzzy sets are always equal is given.

Abstract: This paper studies the problem of distributed multiuser Opportunistic Spectrum Access based on Partially Observable Markov Decision Process (POMDP). Due to the similarity of spectrum environment, secondary users may choose the same channel adopting their own single user approach, which leads to collision. Referring to the previous works, we propose a more flexible and adaptive policy named “threshold-deciding”. Firstly, the SU gets a channel by adopting the random policy. Secondly, the SU decides whether to sense the channel by comparing the available probability with the given threshold. The policy not only decreases the collisions among SUs but also reduces the consumption of time and energy. The simulation results shows that the upgrade of performance is up to 100% compared with the existing random policy, which demonstrate the advantage of the proposed policy.

Abstract: This paper discussed the problem of two dimensional (2D) direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar. The minimum-redundancy linear array (MLRA) is introduced into the transmitting array and receiving array, which enables the high efficiency of the radar system. By utilizing the algorithm of multiple signal classification (MUSIC), we illustrate that the proposed scheme performs better than the uniform linear arrays (ULA) configuration under the same conditions. Simulation results verify the effectiveness of our scheme.

Abstract: Temporomandibular joint (TMJ) is a weight-bearing joint^[1] ,its biomechanical environment is closely related to bite force. Morphological characteristics of occlusal is an important guide to the bite force conduction. This conduction has an important impact on environmental stress in TMJ. Spee curve is one of the important morphological features of dentition,but study of its curvature changes in relations to joint stress is rarely reported . This study aimed to analyze stress distribution in TMJ when curvature of Curve of Spee decreased. In this study, two kinds of 3D model with diffirent curvatures of Curve of Spee were designed. Model 0: the normal, the curvature was 2.50mm. The vertex was at the cuspis of the second premolar. Model 1: the curvature was 0. Then analyzed by 3D-FEM. The final results validated that the anterior surface of condyle and intermediate zone of articular disc were the weight-bearing areas in TMJ. The stress increased along with curvatures of Curve of Spee decreased.

Abstract: Replication technology is a very important data management in cloud storage. Traditional replication control methods cannot usefully solve the load imbalance caused by the hotspot access. This paper proposed a dynamic replication algorithm based on access popularity called APDRA. Replicas were created and deleted dynamically according to the popularity of data, situation of the system and the load of nodes, effectively solving the problem of local overload caused by hot spot access and the recovery of idle replicas. In the end, the superiority of APDRA was verified by experiment.

Abstract: In this paper, a sub-array divided technique using K-means algorithm for spherical conformal array is proposed. All elements of spherical conformal array can be divided into a few sub-arrays by employing the K-means algorithm, and the standard multiple signal classification (MUSIC) algorithm is applied to estimate signals Direction-of-arrival (DOA) on these sub-arrays. Simulations of estimating DOA on a rotational spherical conformal array have been made and the results show that the resolution of DOA is improved by our method compare to existing methods.

Abstract: In order to solve the problems of bat algorithm including low convergence accuracy, slow convergence velocity and easily falling into local optimization, this paper presents an improved bat algorithm based on differential evolution algorithm. The mutation, crossover and selection mechanism of differential evolution algorithm is introduced into bat algorithm, the bat algorithm lack of mutation mechanism has the variation mechanism, so as to enhance the diversity of bat algorithm, the population can avoid falling into local optimum, which enhances the ability of global optimization for bat algorithm. The Simulation results of three standard benchmark functions show that the improved algorithm can greatly improve the convergence precision, convergence speed and robustness, and can effectively discourage the premature convergence.

Abstract: In this paper, a multiple frequency band watermarking algorithm based on stripe image is proposed. The algorithm converts watermark string representing the copyright of image works to stripe image before embedding it to host image. Because of the error correction ability of the stripe image, the algorithm takes on high robustness. This paper also proposed a multiple frequency band embedding strategy through analyzing and classifying various watermark attacking algorithm. Applying this algorithm, watermark can stand several kinds of attacks such as low pass filter and high pass filter. Experimental results show that a blind watermarking algorithm with high robustness to various watermark attacking can be achieved through combining stripe image coding and multiple frequency band strategy.

Abstract: Intrusion detection is one of the most important techniques for protecting network security. In addition, intrusion detection model can be used to recognize real-time pattern, which has important practical significance for real-time intrusion detection. However, due to the sheer speed and scale of the data, data points must often be analyzed in real time. The one-pass-through requirement and the lack of efficient clustering algorithms to identify intrusion patterns limit the power and scalability of this approach. A data stream clustering algorithm is proposed for real-time network intrusion detection. By introducing the new hashing mechanism, the method can quickly find the clustering patterns in the data stream. The method significantly reduces the false alarm rate of intrusion detection, and improves the performance of intrusion detection system.