Machine Learning-Based Analysis of Human Motions for Parkinson’s Disease Diagnostics von Nõmm, S.

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On realizability of neural networks-based input–output models in the classical state-space form von Kotta, Ü., Chowdhury, F.N., Nõmm, S.

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An Alternative Approach to Measure Quantity and Smoothness of the Human Limb Motions von Nõmm, S, Toomela, A

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Preface. Special issue on control and information technology 5th Junior European Meeting; 298 von Nõmm, S

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Partially observed stochastic bilinear system control von Tenno, R., Nomm, S.

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Polynomial based approach in analysis and detection of surgeon's motions von Jakubiak, J., Nomm, S., Vain, J., Miyawaki, F.

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Application of self organizing Kohonen map to detection of surgeon motions during endoscopic surgery von Petlenkov, E., Nomm, S., Vain, J., Miyawaki, F.

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A novel artificial neural networks based automatic adaptive fault detection technique for analog circuits von Petlenkov, E., Jutman, A., Nomm, S., Ubar, R.

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Towards artificial intelligence based automatic adaptive response analyzer for high frequency analog BIST von Petlenkov, E., Jutman, A., Nomm, S., Ubar, R.

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Human-robot interaction learning using timed automata von Vain, J., Miyawaki, F., Nomm, S., Totskaya, T., Anier, A.

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Linear Input-Output Equivalence and Row Reducedness of Discrete-Time Nonlinear Systems von Kotta, Ülle, Bartosiewicz, Z, Nomm, S, Pawluszewicz, E

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REALIZATION OF NONLINEAR DISCRETE-TIME COMPOSITE SYSTEMS: COMPUTATIONAL ASPECTS von Nomm, S., Kotta, Ü., Tonso, M.

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Linearization as a New Approach for the Power Consumption Management of Power Amplifier von Nõmm, S., Moog, C.H., Cottais, E., Wang, Y.

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Reducibility and reduction of discrete-time nonlinear control systems: comparison of two approaches von Kotta, U., Pawluszewicz, E., Nomm, S.

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Extensions of Linear Algebraic Methods to Nonlinear Systems: An Educational Perspective von Moog, C.H., Nõmm, S., Kotta, Ü., Tõnso, M.

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Wearable system for patient motor condition assessment and training monitoring von Kuusik, A., Nomm, S., Ovsjanski, S., Orunurm, L., Reilent, E.

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Identifiability of discrete-time nonlinear systems von Nõmm, S., Moog, C.H.

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Input-Output Equivalence Transformations for Discrete-Time Nonlinear Systems von Bartosiewicz, Z., Kotta, Ü., Nõmm, S., Pawluszewicz, E.

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Realization of Nonlinear Discrete-Time Composite Systems von Nõmm, S., Moog, C.H., Kotta, Ü., Tõnso, M.

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On a New Type of Neural-Network-Based Input-Output Model: The ANARMA Structure von Kotta, Ü., Nõmm, S., Chowdhury, F.N.

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