Results 141 to 150 of about 1,897,301 (192)
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Proceedings of the thirty-third annual ACM symposium on Theory of computing, 2001
Experimental evidence suggests that spectral techniques are valuable for a wide range of applications. A partial list of such applications include (i) semantic analysis of documents used to cluster documents into areas of interest, (ii) collaborative filtering --- the reconstruction of missing data items, and (iii) determining the relative importance ...
Yossi Azar +4 more
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Experimental evidence suggests that spectral techniques are valuable for a wide range of applications. A partial list of such applications include (i) semantic analysis of documents used to cluster documents into areas of interest, (ii) collaborative filtering --- the reconstruction of missing data items, and (iii) determining the relative importance ...
Yossi Azar +4 more
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Proceedings of IEEE International Conference on Evolutionary Computation, 2002
A static analysis method to show the hardness of functions for GAs is shown. It is similar to the Fourier spectral analysis. In the function space, the given function is decomposed to components; each component is a function which concerns only alleles at a combination of loci.
Kazuya Takabatake +2 more
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A static analysis method to show the hardness of functions for GAs is shown. It is similar to the Fourier spectral analysis. In the function space, the given function is decomposed to components; each component is a function which concerns only alleles at a combination of loci.
Kazuya Takabatake +2 more
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Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., 2006
We have seen a surge of interest in spectral-based methods and kernel-based methods for machine learning and data mining. Despite the significant research, these methods remain only loosely related. In this paper, we give theoretically an explicit relation between spectral clustering and weighted kernel principal component analysis (WKPCA).
Fei Wang 0001 +2 more
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We have seen a surge of interest in spectral-based methods and kernel-based methods for machine learning and data mining. Despite the significant research, these methods remain only loosely related. In this paper, we give theoretically an explicit relation between spectral clustering and weighted kernel principal component analysis (WKPCA).
Fei Wang 0001 +2 more
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Electroencephalography and Clinical Neurophysiology, 1983
Spectrum analysis of EMG has gained interest during the past decades due to its quantitative nature. Much of the interest can also be traced back to the greater availability of mini-and microcomputers which enable more elaborate analysis.
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Spectrum analysis of EMG has gained interest during the past decades due to its quantitative nature. Much of the interest can also be traced back to the greater availability of mini-and microcomputers which enable more elaborate analysis.
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SIAM Review, 1981
In this paper we review recent work on the stochastic approach of Walsh spectral analysis. We are mainly interested in the properties of the finite Walsh transform, which in turn allow us to derive...
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In this paper we review recent work on the stochastic approach of Walsh spectral analysis. We are mainly interested in the properties of the finite Walsh transform, which in turn allow us to derive...
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A Generalized Technique for Spectral Analysis
IEEE Transactions on Computers, 1970A technique is presented to implement a class of orthogonal transformations on the order of pN log p N operations. The technique is due to Good [1] and implements a fast Fourier transform, fast Hadamard transform, and a variety of other orthogonal decompositions.
Harry C. Andrews, Kenneth L. Caspari
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Applied Statistics, 1965
A wide variety of applications of spectral analysis have been reported in the literature since spectral estimation methods were introduced by M. S. Bartlett and J. W. Tukey about 15 years ago. In no sense, however, can it be said that spectral analysis is widely used or even understood by statisticians and many of the applications of the technique have
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A wide variety of applications of spectral analysis have been reported in the literature since spectral estimation methods were introduced by M. S. Bartlett and J. W. Tukey about 15 years ago. In no sense, however, can it be said that spectral analysis is widely used or even understood by statisticians and many of the applications of the technique have
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Spectral Analysis and Spectral Synthesis on Polynomial Hypergroups
Monatshefte f�r Mathematik, 2004The author investigates discrete spectral analysis and synthesis for polynomial hypergroups. For this, several well-known facts are reproved. Moreover, some existing literature on the topic, e.g., by R. Lasser and S. Wolfenstetter, is not taken into account.
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SPECTRAL ANALYSIS OF PERTURBED NONQUASIANALYTIC AND SPECTRAL OPERATORS
Russian Academy of Sciences. Izvestiya Mathematics, 1995Summary: Theorems on similarity of perturbed nonquasianalytic (in the sense of Yu. I. Lyubich and V. I. Matsaev) and spectral (in the sense of Dunford) linear operators with countable partition of their spectra to operators of block-diagonal form are obtained.
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2001
Abstract Many pulse EPR experiments are performed by directly or indirectly detecting the free evolution of coherence. The resulting time-domain data contain information on the transition frequencies as we have seen in §§2.2 and 4.2.3. In this chapter we explain how a spectrum is obtained from such time-domain data by FT. For the case of
Arthur Schweiger, Gunnar Jeschke
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Abstract Many pulse EPR experiments are performed by directly or indirectly detecting the free evolution of coherence. The resulting time-domain data contain information on the transition frequencies as we have seen in §§2.2 and 4.2.3. In this chapter we explain how a spectrum is obtained from such time-domain data by FT. For the case of
Arthur Schweiger, Gunnar Jeschke
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