Computational Intelligence in Gait Research: A Perspective on Current Applications and Future Challenges von Lai, D.T.H., Begg, R.K., Palaniswami, M.

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Automatic Recognition of Gait Patterns Exhibiting Patellofemoral Pain Syndrome Using a Support Vector Machine Approach von Lai, D.T.H., Levinger, P., Begg, R.K., Gilleard, W.L., Palaniswami, M.

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A Division Algebraic Framework for Multidimensional Support Vector Regression von Shilton, A., Lai, D.T.H., Palaniswami, M.

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Iterative Fuzzy Support Vector Machine Classification von Shilton, A., Lai, D.T.H.

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Quaternionic and complex-valued Support Vector Regression for Equalization and Function Approximation von Shilton, A., Lai, D.T.H.

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Support Vector Machines for detecting recovery from knee replacement surgery using quantitative gait measures von Levinger, P., Lai, D.T.H., Webster, K., Begg, R.K., Feller, J.

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A nonsmooth optimization approach to sensor network localization von Bagirov, A., Lai, D.T.H., Palaniswami, M.

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Identification of patellofemoral pain syndrome using a Support Vector Machine approach von Lai, D.T.H., Levinger, P., Begg, R.K., Gilleard, W., Palaniswami, M.

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A hybrid Support Vector Machine and autoregressive model for detecting gait disorders in the elderly von Lai, D.T.H., Khandoker, A., Begg, R.K., Palaniswami, M.

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A study of transmission overheads for sensor network localization schemes von Pakkanen, J., Lai, D.T.H.

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The application of multiclass SVM to the detection of knee pathologies using kinetic data: a preliminary study von Levinger, P., Lai, D.T.H., Begg, R., Webster, K., Feller, J., Gilleard, W.

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