This paper presents a block-adaptive subspace algorithm via oblique projection for blind source separation (BSS) problem of convolutive mixtures. In the proposed algorithm, the pro...
The Self-Organizing Map is a popular neural network model for data analysis, for which a wide variety of visualization techniques exists. We present a novel technique that takes th...
Principle Component Analysis (PCA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Desp...
Abstract. This paper presents Artificial Neural Network (ANN) based architecture for underwater object detection from Light Detection And Ranging (Lidar) data. Lidar gives a sequen...
This paper presents two non-parametric statistical test methods, called Kolmogorov-Smirnov (KS) and U statistic test methods, respectively, for informative gene selection of a tumo...
Abstract. Aiming at vehicle tracking with a single moving camera for autonomous driving, this paper presents a strategy of online feature selection combined with related process fr...
Built on the theories of biological neural network, artificial neural network methods have shown many significant advantages. However, the memory space in an artificial neural chip...
It is a challenge to recognize faces under variable poses or illumination directions. In the area of multiview face recognition, many experimental results have shown that the perfo...
Wu-Jun Li, Chong-Jun Wang, Dianxiang Xu, Bin Luo, ...
This paper presents a learning framework for blind source separation (BSS), in which the BSS is formulated as generalized Eigenvalue (GE) problem. Compared to the typical informati...
Abstract. In ISNN’04, a novel symmetric cipher was proposed, by combining a chaotic signal and a clipped neural network (CNN) for encryption. The present paper analyzes the secur...