Abstract To solve the problem of feature extraction in electronic circuits due to nonstationary and nonlinear characteristics fault signals, a method for is proposed, which combines wavelet packet analysis an improved landmark ISOMAP mapping algorithm. The technology used decompose reconstruct signals at multiple levels. extracted entropy construct vector matrix. density-based spatial clusterin...

This report gives an introduction to diffusion maps, some of their underlying theory, as well as their applications in spectral clustering. First, the shortcomings of linear methods such as PCA are shown to motivate the use of graph-based methods. We then explain Locally Linear Embedding [9], Isomap [11] and Laplacian eigenmaps [1], before we give details on diffusion maps and anisotropic diffu...

Most of spectral embedding algorithms such as Isomap, LLE and Laplacian Eigenmap only give map on training samples. One main problem of these methods is to find the embedding of new samples, which is known as the outof-sample problem of spectral embedding. In this paper, we propose a neural network based method to solve this problem. Neural network is used to train and perform both the forward ...

We present the Procrustes measure, a novel measure based on Procrustes rotation that enables quantitative comparison of the output of manifold-based embedding algorithms (such as LLE (Roweis and Saul, 2000) and Isomap (Tenenbaum et al, 2000)). The measure also serves as a natural tool when choosing dimension-reduction parameters. We also present two novel dimension-reduction techniques that att...