14 research outputs found
Study of in the vicinity of
Using 2917 of data accumulated at 3.773~,
44.5~ of data accumulated at 3.65~ and data accumulated
during a line-shape scan with the BESIII detector, the reaction
is studied considering a possible interference
between resonant and continuum amplitudes. The cross section of
,
, is found to have two
solutions, determined to be () pb with the phase angle
(0.11 pb at the 90% confidence level),
or ) pb with both of which
agree with a destructive interference. Using the obtained cross section of
, the cross section of , which is useful information for the future PANDA experiment, is
estimated to be either () nb ( nb at 90% C.L.) or
nb
Isometric Sliced Inverse Regression for Nonlinear Manifolds Learning
[[abstract]]Sliced inverse regression (SIR) was developed to find effective linear dimension-reduction directions for exploring the intrinsic structure of the high-dimensional data. In this study, we present isometric SIR for nonlinear dimension reduction, which is a hybrid of the SIR method using the geodesic distance approximation. First, the proposed method computes the isometric distance between data points; the resulting distance matrix is then sliced according to K-means clustering results, and the classical SIR algorithm is applied. We show that the isometric SIR (ISOSIR) can reveal the geometric structure of a nonlinear manifold dataset (e.g., the Swiss roll). We report and discuss this novel method in comparison to several existing dimension-reduction techniques for data visualization and classification problems. The results show that ISOSIR is a promising nonlinear feature extractor for classification applications.[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子