Finite-dimensional sensor orbits and optimal nonlinear filtering. - James Ting-Ho Lo (IEEE Trans. Inf. Theory, 1972)

On optimal nonlinear estimation part I: Continuous observation. - James Ting-Ho Lo (Inf. Sci., 1973)

On optimal nonlinear estimation – Part II: Discrete observation. - James Ting-Ho Lo (Inf. Sci., 1974)

Signal Detection of Rotational Processes and Frequency Demodulation - James Ting-Ho Lo (Inf. Control., 1974)

Signal detection for bilinear systems. - James Ting-Ho Lo (Inf. Sci., 1975)

A general bayes rule and its application to nonlinear estimation. - James Ting-Ho Lo (Inf. Sci., 1975)

Representation of Continuous Curves on the 3-Dimensional Rotation Group. - James Ting-Ho Lo (Math. Syst. Theory, 1975)

Exponential Fourier densities and optimal estimation and detection on the circle. - James Ting-Ho Lo (IEEE Trans. Inf. Theory, 1977)

Exponential Fourier densities on S2 and optimal estimation and detection for directional processes. - James Ting-Ho Lo; Linda R. Eshleman (IEEE Trans. Inf. Theory, 1977)

Exponential Fourier densities and optimal estimation for axial processes. - James Ting-Ho Lo; Linda R. Eshleman (IEEE Trans. Inf. Theory, 1979)

Eigenstructure methods for array sensor localization. - James Ting-Ho Lo; Stanley Lawrence Marple Jr. (ICASSP, 1987)

Optimal functional expansion for estimation from counting observations. - James Ting-Ho Lo; Sze-Kui Ng (IEEE Trans. Inf. Theory, 1987)

New maximum likelihood approach to multiple signal estimation. - James Ting-Ho Lo (ICASSP, 1988)

Array sensor localization and calibration by cyclic regression. - James Ting-Ho Lo (ICASSP, 1990)

Backestimation for training multilayer perceptrons. - James Ting-Ho Lo (ICASSP, 1991)

Observability conditions for multiple signal direction finding and array sensor localization. - James Ting-Ho Lo; Stanley Lawrence Marple Jr. (IEEE Trans. Signal Process., 1992)

Recursive direction finding in the presence of sensor array uncertainties. - Joseph H. Clements III; James Ting-Ho Lo (ICASSP (4), 1993)

Synthetic approach to optimal filtering. - James Ting-Ho Lo (IEEE Trans. Neural Networks, 1994)

Adaptive system identification by nonadaptively trained neural networks. - James Ting-Ho Lo (ICNN, 1996)

Robust adaptive identification of dynamic systems by neural networks. - James Ting-Ho Lo (ICNN, 1997)

Robust adaptive neurofilters with or without online weight adjustment. - James Ting-Ho Lo (ICNN, 1997)

Overcoming recurrent neural networks' compactness limitation for neurofiltering. - James Ting-Ho Lo; Lei Yu (ICNN, 1997)

Probabilistic associative memories. - James Ting-Ho Lo (IJCNN, 2008)

Adaptive Capability of Recurrent Neural Networks with Fixed Weights for Series-Parallel System Identification. - James Ting-Ho Lo (Neural Comput., 2009)

Unsupervised Hebbian learning by recurrent multilayer neural networks for temporal hierarchical pattern recognition. - James Ting-Ho Lo (CISS, 2010)

Convexification for data fitting. - James Ting-Ho Lo (J. Glob. Optim., 2010)

A low-order model of biological neural networks for hierarchical or temporal pattern clustering, detection and recognition. - James Ting-Ho Lo (IJCNN, 2011)

A Low-Order Model of Biological Neural Networks. - James Ting-Ho Lo (Neural Comput., 2011)

Overcoming the Local-Minimum Problem in Training Multilayer Perceptrons with the NRAE Training Method. - James Ting-Ho Lo; Yichuan Gui; Yun Peng 001 (ISNN (1), 2012)

A cortex-like learning machine for temporal hierarchical pattern clustering, detection, and recognition. - James Ting-Ho Lo (Neurocomputing, 2012)

Overcoming the local-minimum problem in training multilayer perceptrons by gradual deconvexification. - James Ting-Ho Lo; Yichuan Gui; Yun Peng 001 (IJCNN, 2013)

Overcoming the Local-Minimum Problem in Training Multilayer Perceptrons with the NRAE-MSE Training Method. - James Ting-Ho Lo; Yichuan Gui; Yun Peng 001 (ISNN (1), 2013)

A pairwise algorithm for training multilayer perceptrons with the normalized risk-averting error criterion. - Yichuan Gui; James Ting-Ho Lo; Yun Peng 001 (IJCNN, 2014)

The normalized risk-averting error criterion for avoiding nonglobal local minima in training neural networks. - James Ting-Ho Lo; Yichuan Gui; Yun Peng 001 (Neurocomputing, 2015)

Accommodative neural filters. - James Ting-Ho Lo; Yu Guo 006 (IJCNN, 2016)

Training deep neural networks with gradual deconvexification. - James Ting-Ho Lo; Yichuan Gui; Yun Peng 001 (IJCNN, 2016)

Nonlinear system identification based on recurrent neural networks with shared and specialized memories. - Yu Guo 006; Fei Wang 008; James Ting-Ho Lo (ASCC, 2017)

A neural filter-based scheme for synchronizing chaotic systems. - Yu Guo 006; Fei Wang 008; James Ting-Ho Lo (ICASSP, 2017)

Solving the Local-Minimum Problem in Training Deep Learning Machines. - James Ting-Ho Lo; Yichuan Gui; Yun Peng 001 (ICONIP (1), 2017)

Chaotic synchronization based on neural filter. - Yu Guo 006; Fei Wang 008; James Ting-Ho Lo (J. Frankl. Inst., 2018)

Low-Order Model of Biological Neural Networks. - Huachuan Wang; James Ting-Ho Lo (CoRR, 2020)

Adaptively Solving the Local-Minimum Problem for Deep Neural Networks. - Huachuan Wang; James Ting-Ho Lo (CoRR, 2020)