34540225
A Region-Based Image Enhancement Algorithm with the Grossberg Network
In order to enhance the contrast of an image, histogram equalization is wildly used. With global histogram equalization (GHE), the image is enhanced as a whole, and this may induce some areas to be overenhanced or blurred. Although local histogram equalization (LHE) acts adaptively to overcome this problem, it brings noise and artifacts to image. In this paper, a region-based enhancement algorithm is proposed, in which Grossberg network is employed to generate histogram and extract regions. Simulation results show that the image is obviously improved with the advantage of both GHE and LHE.
35232477
On Robust Stability of BAM Neural Networks with Constant Delays
The problems of determining the robust stability of bidirectional associative memory neural networks with delays are investigated in this paper. An approach combining the Lyapunov-Krasovskii stability theorem with the linear matrix inequality (LMI) technique is taken to study the problems, which provide bounds on the interconnection matrix and the activation functions. Some criteria for the robust stability, which give information on the delay-independence property, are derived. The results obtained in this paper provide one more set of easily verified guidelines for determining the robust stability of delayed BAM (DBAM) neural networks, which are less conservative and less restrictive than the ones reported recently in the literature. Some typical examples are presented to show the effectiveness of results.
12301426
A Novel Symmetric Cryptography Based on Chaotic Signal Generator and a Clipped Neural Network
Recently, a novel encryption algorithm that integrates Haar wavelets transformation into chaotic signal generator, was proposed by R.Luo et al. In this paper, we first analyzed the merits and demerits of this algorithm. Then an improved scheme which uses a clipped neural network is proposed. Both theoretical analysis and computer simulations show our proposed scheme succeeds in overcoming the defects of Luo’s algorithm while retaining all its merits. Moreover, the way that the clipped neural network evolves may present a new idea to the cryptography.
15834568
An Artificial Neural Network Based on CIEA
Chaotic Immune evolutionary algorithm (CIEA) is proposed on the shortage of current algorithms training artificial neural network, biological immune mechanism and the characteristics of evolution. A novel artificial neural network based on chaotic immune evolutionary algorithm (CIEANN) is presented in this paper. The algorithm has the merits of chaos, immunity and evolutionary algorithm. It can ensure the ability of global search and local search and enhance the performances of the algorithm. At last, we analyzed the performance of CIEANN with a typical XOR problem and compared it with several common ANNs. The analysis results show that CIEANN converges quickly and avoids immature convergence and is an effective way to solve optimization problem.
21338568
Research on Risk Probability Estimating Using Fuzzy Clustering for Dynamic Security Assessment
Effective network security management requires assessment of inherently uncertain events and circumstances dynamically. This paper addresses the problems of risk probability assessment and presents an alternative approach for estimating probability of security risk associated with some interaction in ubiquitous computing. A risk probability assessment formula is proposed, and an estimating model adopting the Fuzzy C-Means clustering algorithm is presented. An experiment based on DARPA intrusion detection evaluation data is given to support the suggested approach and demonstrate the feasibility and suitability for use. The practices indicate that fuzzy clustering technique provides concepts and theoretical results that are valuable in formulating and solving problems in dynamic security assessment.
19656381
Target Recognition of FLIR Images on Radial Basis Function Neural Network
The study of small target recognition in low SNR (Signal Noise Ratio) is the key problem about processing of forward-looking infrared (FLIR) images information. Eight features of objects based on IR radiation characteristics and wavelet-based are presented. These features are used to a radial basis function (RBF) network as input for learning and classification. The propose recognition algorithm is invariant to the translation, rotation, and scale channel of a shape. Experiments by real infrared images and noisy images are performed, and recognition results show that the method is very effective.
20327796
An effective algorithm of motif finding problem
Identification of the short DNA sequence motif, which serves as binding targets for transcription factors, is a fundamental problem in both computer science and molecular biology. Especially, finding the subtle motifs with variable gaps is more challenging. In this paper, a new algorithm is presented, which explores some new strategies. Based on a neighbourhood set concept, a new probability matrix is defined, which can capture the target motifs effectively. An iterative restart strategy is used, by which we can use several similar motifs' information to detect the real motif to demonstrate the effectiveness of our algorithm. We test it on several kinds of data and compare it with some other current representation algorithms. Simulation shows that the algorithm can effectively detect the subtle motifs.
20311666
CoStore: a storage cluster architecture using network attached storage devices
We propose a storage cluster architecture CoStore, which evenly distributes system responsibilities across all collaborating cluster members without a separate central file manager. The serverless CoStore architecture has the potential to provide scalable high-performance high-capacity storage services with strong reliability and availability, traditionally only achievable by high-end storage systems. A prototype CoStore system has been implemented using cost-effective COTS-based network attached storage devices on commodity operating systems. The performance of the CoStore prototype has been measured and compared with those of other commonly available distributed file systems. Preliminary test results show that a single node CoStore has a comparable performance to that of NFS and that CoStore outperforms CIFS on Windows 2000.