It is shown in detail how recent advances in multiple-output and projectional quantile regression open the door to exact computation of many inferential statistics based on projection pursuit. This is also illustrated on a few examples including new regression generalizations of multivariate skewness, kurtosis and projection depth. Note: The following files were submitted by the author for peer...

Hyperspectral data potentially contain more information than multispectral data because of their higher spectral resolution. However, the stochastic data analysis approaches, successfully applied to classification of multispectral data, are not as effective as those for hyperspectral data. Various investigations indicate that the key problem causing poor performance in the stochastic approaches...

Two projection based feedforward network learning methods for modelfree regression problems are studied and compared in this paper: one is the popular back-propagation learning (BPL); the other is the projection pursuit learning (PPL). Unlike the totally parametric BPL method, the PPL non-parametrically estimates unknown nonlinear functions sequentially (neuron-by-neuron and layer-by-Iayer) at ...

Projection pursuit index measuring quality of projected clusters (QPC) introduced recently optimizes projection directions by minimizing leave-one-out error searching for pure localized clusters. QPC index has been used in constructive neural networks to discover non-local clusters in high-dimensional multiclass data, reduce dimensionality, aggregate features, visualize and classify data. Howev...

This paper established a conservation tillage evaluation model based on projection pursuit to evaluate the soil composite achievement of conservation tillage. After optimizing the project direction, the multi-dimension data of the seven evaluation indices are synthesized to one dimension, and the author could evaluate each item with the projection data easily, which avoided the jamming of weigh...

Detection, Synchronization, Channel Estimation and Capacity in UWB Sensor Networks using Compressed Sensing by Shao-Yuan Chen Chair: Wayne E. Stark Conventional receivers in ultrawideband (UWB) communication system usually require high sampling rate and thus consume much power. With compressed sensing (CS), the sampling rate can potentially be reduced. In this thesis, the performance of CS used...

In this paper, we propose a clustering technique for the recognition of pigmented skin lesions in dermatological images. It is known that computer vision-based diagnosis systems have been used aiming mostly at the early detection of skin cancer and more specifically the recognition of malignant melanoma tumor. The feature extraction is performed utilizing digital image processing methods, i.e. ...