In line with the pressures of energy shortage and economic development, Chinese government has adopted a series of measures and policies to promote the exploitation and utilization efficiency of electric power. China is urgently reconsidering its electric power development level and coordinating between power supply and demand sides. Therefore, in this paper, Chinese industrial structure of ele...

Projection pursuit is the search for interesting low-dimensional projections of high-dimensional data. It optimizes projection indices, which increase with the interestingness of the projection image. Most classical approaches equate interestingness with non-gaussianity. However, in cluster analysis one should more be interested in departure from unimodality. The dip is an efficient nonparametr...

Compressive sensing (CS) is mainly concerned with low-coherence pairs, since the number of samples needed to recover the signal is proportional to the mutual coherence between projection matrix and sparsifying matrix. Until now, papers on CS always assume the projection matrix to be a random matrix. In this paper, aiming at minimizing the mutual coherence, a method is proposed to optimize the p...

Exploratory projection pursuit is a method for finding interesting projections of highdimensional multivariate data sets. Typically interesting projections are found by numerically optimizing a measure of non-normality over projection direction. In general, explicit computation of a projection index is impossible although for certain restricted situations an index may be computed analytically. ...

Projection pursuit learning networks (PPLNs) have been used in many elds of research but have not been widely used in image processing. In this paper we demonstrate how this highly promising technique may be used to connect edges and produce continuous boundaries. We also propose the application of PPLN to deblurring a degraded image when little or no apriori information about the blur is avail...

Learning from data with complex non-local relations and multimodal class distribution for widely used classification algorithms is still very hard. Even if accurate solution is found the resulting model may be too complex for a given data and will not generalize well. New types of learning algorithms are needed to extend capabilities of standard machine learning systems. Projection pursuit meth...

Evoked response potentials (ERPs) to brief flashes of light were analyzed for constituent features that could be used to distinguish individuals with Alzheimer's disease (AD, n = 15) from matched control subjects (n = 17). Statistical k nearest-neighbor methods distinguished AD from control with a maximum sensitivity of 29% and false alarm rate of 12%. The comparable sensitivity/false-alarm val...