Dongxin Xu, Craig Fancourt, Chuan Wang
In speech recognition, the speech signal is usually represented in multidimensions but the Hidden Markov Model (HMM) is one-dimensional. In this paper, a Multi-Channel HMM (MC-HMM) is proposed as a...
header for SPIE use From Hyperplanes to Large Margin Classifiers: Applications to SAR ATR (2007)
Qun Zhao, Jose C. Principe, Dongxin Xu
In this paper, the structural risk minimization (SRM) criterion is employed to train a large margin classifier, the support vector machine (SVM). Its relative performance is compared with traditional...
Qun Zhao, Victor Brennan, Dongxin Xu, Zheng Wang, Jose C. Principe, Jose C. Principe, ...
This paper describes a new architecture for synthetic aperture radar (SAR) automatic target recognition (ATR) based on the premise that the pose of the target is estimated within a high degree of...
Information-Theoretic Learning Using Renyi's Quadratic Entropy (1999)
Learning from examples has been traditionally based on correlation or on the mean square error (MSE) criterion, in spite of the fact that learning is intrinsically related with the extraction of...
Training MLPs Layer-by-Layer with the Information Potential (1999)
In the area of information processing one fundamental issue is how to measure the statistical relationship between two variables based only on their samples. In a previous paper, the idea of...
Information-Theoretic Learning (1999)
This chapter seeks to extend the ubiquitous mean-square error criterion (MSE) to cost functions that include more information about the training data. Since the learning process ultimately should...
Information-Theoretic Learning Using Renyi's Quadratic Entropy (1999)
Jose Principe Dongxin, Jose C. Principe, Dongxin Xu
Learning from examples has been traditionally based on correlation or on the mean square error (MSE) criterion, in spite of the fact that learning is intrinsically related with the extraction of...
Principe J.: Training MLPs layer-by-layer with the information potential (1999)
In the area of information processing one fundamental issue is how to measure the statistical relationship between two variables based only on their samples. In a previous paper, the idea of...
Learning from examples with Information Theoretic Criteria (1999)
Jose C. Principe, Dongxin Xu, Qun Zhao
This paper discusses a framework for learning based on information theoretic criteria. A novel algorithm based on Renyi’s quadratic entropy is used to train, directly from a data set, linear or...
Learning from examples with Information Theoretic Criteria (1999)
Jose C. Principe, Dongxin Xu, Qun Zhao
This paper discusses a framework for learning based on information theoretic criteria. A novel algorithm based on Renyi’s quadratic entropy is used to train, directly from a data set, linear or...
Learning From Examples with Quadratic Mutual Information (1998)
this paper, a Quadratic Mutual Information measure for a set of discrete samples is introduced and a brief description of the learning algorithm is presented.
Learning from Examples with Quadratic Mutual Information (1998)
This paper discusses a novel algorithm to train nonlinear mappers with information theoretic criteria (entropy or mutual information) directly from a training set. The method is based on a Parzen...
Pose Estimation in SAR using an Information Theoretic Criterion (1998)
This paper describes a pose estimation algorithm based on an information theoretic formulation. We formulate the pose estimation statistically and show that pose can be estimated from a low...
Pose Estimation for SAR Automatic Target Recognition (1998)
Qun Zhao, Dongxin Xu, Jose C. Principe
1 This paper explores statistically pose estimation in SAR ATR. Based on our proposed method of maximizing mutual information, further experiments are conducted by using the MSTAR/IU Database....
Pose estimation of SAR automatic target recognition (1998)
Qun Zhao, Dongxin Xu, Jose C. Principe
This paper explores statistically pose estimation in SAR ATR. Based on our proposed method of maximizing mutual information, further experiments are conducted by using the new MSTAR/ IU Database....
A Novel Measure for Independent Component Analysis (ICA)
Dongxin Xu, Jose C. Principe, John Fisher, John Fisher Iii, Hsiao-Chun Wu
Measures of independence (and dependence) are fundamental in many areas of engineering and signal processing. Shannon introduced the idea of Information Entropy which has a sound theoretical...