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The following topics are dealt with: learning theory; learning algorithm; evolutionary computation; data mining; distributed system; multi-agent system; image processing; pattern recognition; fuzzy system; cryptography; system security; watermarking and information hiding.
The use of Digital Rights Management (DRM) technologies for the enforcement of digital media usage models is currently subject of a heated debate. Consumer organizations and national governments claim that DRM technology interferes with basic personal rights, such as the right to make copies for personal use or the right to use content on any platform of choice. This issue has lately gained increased...
Real-world data are dirty, and therefore, noise handling is a defining characteristic for data mining research and applications. This talk will review existing research efforts on data cleansing and classifier ensembling in dealing with random noise, and then present our recent research on an error aware data mining design to process structured noise. This error aware data mining framework makes use...
Summary form only given. Tactical networks frequently need to be set up without adequate infrastructure in place or where infrastructure elements can be destroyed easily and, moreover, must themselves be mobile and extensible. It is therefore desirable to provide mechanisms based on mobile ad hoc networks, which have been studied intensely in recent years. However, the specific requirements for tactical...
This paper presents a new algorithm for recovering of the mixing matrix A of underdetermined source separation. Most of the existing algorithms for SCA assume that souce signals are strictly sparse, but the condition in this paper has been relaxed, i.e., there could be at most m-1 nonzero elements of the source signals in each time. Firstly, we can find that all m-1 linearly independent column vectors...
Since soil erosion is a serious environmental problem, regional-scale soil erosion assessment is important. However, it is limited by the development of soil erosion mode by far. This paper presents a region- scaled soil erosion qualitative evaluation model based on naive Bayes. Firstly, the model takes the E'Dong Mountain as case study area, chooses the four factor indexes affected erosion intensity,...
We describe an Early Warning System (EWS) which enables the root cause analysis for initiating quality improvements in the manufacturing shop floor and process engineering departments, at product OEMs as well as their tiered suppliers. The EWS combines the use of custom designed domain ontology of manufacturing processes and failure related knowledge, innovative application of domain knowledge in...
Aiming at the problem of blind source separation of the communication signals, we propose a step size optimization equivariant adaptive source separation via independence (SO-EASI) algorithm basing on the EASI block based algorithm. This algorithm adjusts the step-size by the steepest descent method and thereby greatly increases its convergence speed whatever value the step-size is initialized. Simulation...
A novel variable step-size online algorithm for mixed signals with sub- and super-Gaussian source distributions based on the extended infomax is present. The extended infomax algorithm usually separates the sources by batch processing and it requires adequate samples to estimate the kurtosis of the output signals so the algorithm will be invalid when the channel matrix is changed. An improved online...
It is very difficult for the adaptive neuro-fuzzy interference system (ANFIS) using conventional training methods to converge while the samples space distribution is more complex, the desired results for that couldn't be achieved. To change the situation and improve the learning behavior of ANFIS, in this paper we propose a new self-adaptive learning algorithm for ANFIS differently from conventional...
For the complexity of the automation system roll on, sensors should have to be more intelligent. Recently, Neural Network is widely used to intelligentize sensors for its well performance on capturing the information of the data. But due to its intrinsic linear character, it doesn't perform well in nonlinear data processing. In this paper, RNN with Kernel Principal Component Analysis (KPCA) and Principal...
Question classification is one of the most important sub- tasks in Question Answering systems. Now question tax- onomy is getting larger and more fine-grained for better answer generation. Many approaches to question classifi- cation have been proposed and achieve reasonable results. However, all previous approaches use certain learning al- gorithm to learn a classifier from binary feature vectors,...
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