Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Shien-Ching Hwang"'
Autor:
Shien-Ching Hwang, 黃賢卿
88
The butterfly graphs were originally introduced as the underlying graphs of FFT networks which can perform the fast Fourier transform (FFT) very efficiently. Besides, the butterfly graphs belong to the class of Cayley graphs which are suitabl
The butterfly graphs were originally introduced as the underlying graphs of FFT networks which can perform the fast Fourier transform (FFT) very efficiently. Besides, the butterfly graphs belong to the class of Cayley graphs which are suitabl
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/32027472939035743304
Autor:
Chien-Yu Chen1 cychen@mars.csie.ntu.edu.tw, Shien-Ching Hwang1 schwang@mars.csie.ntu.edu.tw, Yen-Jen Oyang1 yjoyang@csie.ntu.edu.tw
Publikováno v:
Intelligent Data Analysis. 2005, Vol. 9 Issue 1, p43-57. 15p. 6 Charts, 2 Graphs.
Publikováno v:
Biomedical Engineering: Applications, Basis and Communications. 22:385-391
The B-factor, which is also known as temperature factor or Debby–Waller factor, is an important structural flexibility index of the ground-state protein conformation. In particular, the B-factors associated with a segment of residues, reflect the l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d82c3266bd3ad24251a16fd37bb0a5d
https://doi.org/10.4015/s1016237210002146
https://doi.org/10.4015/s1016237210002146
Publikováno v:
Pattern Recognition. 38:2256-2269
As the sizes of many contemporary databases continue to grow rapidly, incremental clustering has emerged as an essential issue for conducting data analysis on contemporary databases. An incremental clustering algorithm refers to an abstraction of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e0f1487d162b0b05e62440700902d6d
https://doi.org/10.1016/j.patcog.2005.03.005
https://doi.org/10.1016/j.patcog.2005.03.005
Publikováno v:
IEEE Transactions on Neural Networks. 16:225-236
This work presents a novel learning algorithm for efficient construction of the radial basis function (RBF) networks that can deliver the same level of accuracy as the support vector machines (SVMs) in data classification applications. The proposed l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f539d058f613bb4f270fa729032973d
https://doi.org/10.1109/tnn.2004.836229
https://doi.org/10.1109/tnn.2004.836229
Autor:
Gen-Huey Chen, Shien-Ching Hwang
Publikováno v:
Networks. 37:156-164
Given a connected graph G, a spanning subgraph G′ of G is called a t-spanner if every pair of two adjacent vertices in G has a distance of at most t in G′. A t-spanner of a graph G is minimum if it contains minimum number of edges among all t-spa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4955b8074dc92b9f4bfff49e5fa7556
https://doi.org/10.1002/net.5
https://doi.org/10.1002/net.5
Autor:
Gen-Huey Chen, Shien-Ching Hwang
Publikováno v:
Information Processing Letters. 72:131-135
Fu and Chau have proposed a new family of Cayley graphs, named cyclic-cubes. In this note we show that cyclic-cubes are isomorphic to the well-known wrap-around butterfly graphs.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87c420fdeff8dce9abdf3e86f0503574
https://doi.org/10.1016/s0020-0190(99)00138-6
https://doi.org/10.1016/s0020-0190(99)00138-6
Publikováno v:
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..
In recent years, kernel density estimation has been exploited by computer scientists to model several important problems in machine learning, bioinformatics, and computer vision. However, in case the dimension of the data set is high, then the conven
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a55762c47764721efcf2120fd2ae861
https://doi.org/10.1109/ijcnn.2005.1556374
https://doi.org/10.1109/ijcnn.2005.1556374
Publikováno v:
Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..
This paper proposes a novel learning algorithm for constructing data classifiers with radial basis function (RBF) networks. The RBF networks constructed with the proposed learning algorithm generally are able to deliver the same level of classificati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3312e9a62028bbc1323dc6cb0741b9e7
https://doi.org/10.1109/iconip.2002.1198215
https://doi.org/10.1109/iconip.2002.1198215
Autor:
Shien-Ching Hwang, Yen-Jen Oyang
Publikováno v:
Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..
This paper proposes a novel learning algorithm for constructing function approximators with radial basis function (RBF) networks. In comparison with the existing learning algorithms, the proposed algorithm features lower time complexity for construct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b099f4e083f575f204433c5fe83aa15
https://doi.org/10.1109/iconip.2002.1198218
https://doi.org/10.1109/iconip.2002.1198218