Unsupervised learning in neural computation
Theoretical Computer Science - Natural computing
Financial APT-Based Gaussian TFA Learning for Adaptive Portfolio Management
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Mining Dependence Structures from Statistical Learning Perspective
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
BYY harmony learning, structural RPCL, and topological self-organizing on mixture models
Neural Networks - New developments in self-organizing maps
Data smoothing regularization, multi-sets-learning, and problem solving strategies
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
Arbitrage pricing theory-based Gaussian temporal factor analysis for adaptive portfolio management
Decision Support Systems - Special issue: Data mining for financial decision making
Improved system for object detection and star/galaxy classification via local subspace analysis
Neural Networks - 2003 Special issue: Neural network analysis of complex scientific data: Astronomy and geosciences
A comparative investigation on subspace dimension determination
Neural Networks - 2004 Special issue: New developments in self-organizing systems
A maximum likelihood approach to temporal factor analysis in state-space model
Signal Processing - Fractional calculus applications in signals and systems
IEEE Transactions on Signal Processing
Optimizing financial portfolios from the perspective of mining temporal structures of stock returns
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Bayesian Ying Yang system, best harmony learning, and Gaussian manifold based family
WCCI'08 Proceedings of the 2008 IEEE world conference on Computational intelligence: research frontiers
| Hi-index | 35.69 |
The temporal Bayesian Yang-Yang (TBYY) learning has been presented for signal modeling in a general state space approach, which provides not only a unified point of view on the Kalman filter, hidden Markov model (HMM), independent component analysis (ICA), and blind source separation (BSS) with extensions, but also further advances on these studies, including a higher order HMM, independent HMM for binary BSS, temporal ICA (TICA), and temporal factor analysis for real BSS without and with noise. Adaptive algorithms are developed for implementation and criteria are provided for selecting an appropriate number of states or sources. Moreover, theorems are given on the conditions for source separation by linear and nonlinear TICA. Particularly, it has been shown that not only non-Gaussian but also Gaussian sources can also be separated by TICA via exploring temporal dependence. Experiments are also demonstrated