We propose two methods of analysis of chaotic processes to be applied insensory analysis. These methods may be used off-line in clinics e.g. for analysis ofbiosignals registered during sleep, or implemented into new sensor systems e.g. fordrivers' vigilance monitoring in real time; they may also be applied in new type ofhybrid models of circulatory and respiratory systems.
Mathematical analysis, and in particular Harmonic Analysis, has tradi-tionally been tied to physical modeling - providing the language to describe the infinitesimal laws of nature through calculus arid partial differential ex-pressions as well as descriptions of field effects through integral operators, spectral and functional analysis.
The paper focused on the service loads and cumulative damage analysis. The description of theservice load contains: the examples of statistical analysis of random stress process, stress spectrumand stress program.
This chapter provides a commented list of references which the author considers useful for diffraction data analysis such as references relating to Rietveld analysis. In particular, references relating to the analysis of two-dimensional detector data such as image plates or CCDs are given. Literature dealing with texture analysis and interpretation as well as web links for software and online tutorials are also provided.
The 'analysis on fractals' and 'analysis on metric spaces' communities have tended to work independently. Metric spaces such as the Sierpinski carpet fail to satisfy some of the properties which are generally assumed for metric spaces. This survey discusses analysis on the Sierpinski carpet, with particular emphasis on the properties of the heat kernel.
Dynamic program analysis is a very popular technique for analysis of computer programs. It analyses the properties of a program while it is executing. Dynamic analysis has been found to be more precise than static analysis in handling run-time features like dynamic binding, polymorphism, threads etc. Therefore much emphasis is now being given on dynamic analysis of programs ( instead of static analysis) involving the above mentioned features. Various techniques have been devised over the past several years for the dynamic analysis of programs. This paper provides an overview of the existing techniques and tools for the dynamic analysis of programs. Further, the paper compares these techniques for their merits and demerits and emphasizes the importance of each technique.
In this paper, a kernelized version of nonparametric discriminant analysis is proposed that we name KNDA. The main idea is to first map the original data into another highdimensional space, and then to perform nonparametric discriminant analysis in the high dimensional space. Nonparametric discriminant analysis can relax the Gaussian assumption required for the classical linear discriminant analysis, and Kernel trick can further improve the separation ability. A group of tests on several UCI standard benchmarks have been carried out that prove our proposed method is very promising.
Fault Tree Analysis (FTA) is one of the most important analysis method of safety system engineering, the FTA can finish the qualitative analysis and the quantitative analysis, the consequences of accidents described with FTA are intuitional, intelligible, clear and logical, is now the recognized practical methods to the security and reliability analysis of complex system. In this paper, based on advanced computer theory and technology, combined with fault tree analysis method, determine the system functions, completes the design of system structure, furthermore, the integrated analysis environment that combines the Fault Tree graph creation and Fault Tree dynamic analysis is constructed based on computer. The FTA analysis system supplies high efficiency and correct technology and measures for accidents analysis and safely assessment.