James Ting-Ho Lo's Selected Publications


Convexification and Deconvexification for solving the local-minimum problem

A paper that reports progress toward to the deconvexification method for solving the local-minimum problem are listed below. The paper on the deconvexification will be included as soon as it is published.

Overcoming the Local-Minimum Problem in Training Multilayer Perceptrons with the NRAE Training Method, J. T.-H. Lo, Y. Gui and Y. Peng; Advances in Neural Networks - ISNN 2012, J. Wang, G.G. Yen, and M.M. Polycarpou (Eds.), pp. 440-447, Springer-Verlag Berlin Heidelberg, 2012.

Convexification for Data Fitting, J. T.-H. Lo; Journal of Global Optimization, Vol. 46, pp. 307-315, February 2010.


Models of biological neural networks and cortex-like learning machines

A Cortex-Like Learning Machine for Temporal Hierarchical Pattern Clustering, Detection, and Recognition, J. T.-H. Lo; Neurocomputing, Vol. 78, pp. 89-103, 2012.

A Low-Order Model of Biological Neural Networks, J. T.-H. Lo; Neural Computation, Vol. 23, No. 10, pp. 2626-2682, 2011.

A Low-Order Model of Biological Neural Networks for Hierarchical or Temporal Pattern Clustering, Detection and Recognition, J. T.-H. Lo; Proceedings on the 2011 International Joint Conference on Neural Networks, IEEE Xplore, The IEEE Press, 2011.

Functional Model of Biological Neural Networks, J. T.-H. Lo; Cognitive Neurodynamics, Vol. 4, No. 4, pp. 295-313, November 2010.

Unsupervised Hebbian learning by recurrent multilayer neural networks for temporal hierarchical pattern recognition, J. T.-H. Lo; Proceedings of the 44th Annual Conference on Information Systems and Sciences, March 2010.

Probabilistic Associative Memories, J. T.-H. Lo; Proceedings of the 2008 International Joint Conference on Neural Networks, pp. 3895 - 3903, IEEE Xplore, The IEEE Press, August 2008.


Neural network approach to adaptive processing

Adaptive Capability of Recurrent Neural Networks with Fixed Weights for Series-Parallel System Identification, J. T.-H. Lo; Neural Computation, Vol. 21, No. 11, pp. 3214-3227, 2009.

Adaptive Neural Filters, J. T.-H. Lo and J. Nave; Proceedings of the 2007 International Joint Conference on Neural Networks, pp. 2147 - 2152, IEEE Xplore, The IEEE Press, August 2007.

Adaptive versus Accommodative Neural Networks for Adaptive Series-Parallel Identification of Dynamical Systems, Part II, J. T.-H. Lo and D. Bassu; Proceedings of the 2003 International Joint Conference on Neural Networks, Volume 4, pp. 2497 - 2501, IEEE Xplore, The IEEE Press, July 2003.

Adaptive Parallel Identification of Dynamical Systems with Uncertain Stable and Periodic Trajectories, J. T.-H. Lo and D. Bassu; Proceedings of the 2003 International Joint Conference on Neural Networks, Vol. 2, pp. 914-918, IEEE Xplore, The IEEE Press, July 2003.

Adaptive Series-Parallel Identification of Dynamical Systems with Uncertain Bifurcations and Chaos, J. T.-H. Lo and D. Bassu; Proceedings of the 2003 International Joint Conference on Neural Networks, Vol. 2, pp. 1553-1557, IEEE Xplore, The IEEE Press, July 2003.

Mathematical Underpinning of Adaptive Capability of Recurrent Neural Networks with Fixed Weights, J. T.-H. Lo; Proceedings of the 2003 International Joint Conference on Neural Networks, Vol. 2, pp. 1541-1546, IEEE Xplore, The IEEE Press, July 2003.


Robust Processing

Existence and Uniqueness of Risk-Sensitive Estimation, J. T.-H. Lo and T. Wanner; IEEE Transactions on Automatic Control, pp. 1945-1948, November 2002.

Robust Identification of Uncertain Dynamical Systems where Adaptation is Impossible, J. T.-H. Lo and D. Bassu; Proceedings of the 2002 International Joint Conference on Neural Networks, vol. 2, pp. 1558-1563, IEEE Xplore, The IEEE Press, May 2002.

Robust Approximation of Uncertain Functions where Adaptation is Impossible J. T.-H. Lo and D. Bassu; Proceedings of the 2002 International Joint Conference on Neural Networks, vol. 2, pp. 1956-1961, IEEE Xplore, The IEEE Press, May 2002.

Robust Identification of Dynamical Systems by Neurocomputing, J. T.-H. Lo and D. Bassu; Proceedings of the 2001 International Joint Conference on Neural Networks, Vol. 2, pp. 1285-1290, IEEE Xplore, The IEEE Press, July 2001.

Mathematical Justification of Risk-Sensitive Neural Filtering, J. T.-H. Lo; Proceedings of the 2000 Conference on Information Sciences and Systems, Vol. I, pp. WA1-7 - WA1-11, Princeton, New Jersey, 2000.


Neural Filtering

Neural Filtering J. T.-H. Lo; Scholarpedia, Vol. 4, No. 8, page 7868, 2009.

Adaptive Neural Filters J. T.-H. Lo and J. Nave; Proceedings of the 2007 International Joint Conference on Neural Networks, pp. 2147-2152, IEEE Xplore, The IEEE Press, August 2007.

Recursive Neural Filters and Dynamical Range Transformers, J. T.-H. Lo and L. Yu; Proceedings of The IEEE, Vol. 92, No. 3, pp. 514-535, March 2004.

Synthetic Approach to Optimal Filtering, J. T.-H. Lo; IEEE Transactions on Neural Networks, Vol. 5, No. 5, pp. 803-811, September 1994.