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- Jeremy L Emken, Raul Benitez, Athanasios Sideris, James E Bobrow, David J Reinkensmeyer
- Journal of neurophysiology
- 2007

Motor adaptation to a novel dynamic environment is primarily thought of as a process in which the nervous system learns to anticipate the environmental forces to eliminate kinematic error. Here we show that motor adaptation can more generally be modeled as a process in which the motor system greedily minimizes a cost function that is the weighted sum of… (More)

- Yiu-Fai Wong, Athanasios Sideris
- IEEE Trans. Neural Networks
- 1992

A new way to look at the learning algorithm in the cerebellar model articulation controller (CMAC) proposed by J.S. Albus (1975) is presented. A proof that the CMAC learning always converges with arbitrary accuracy on any set of training data is obtained. An alternative way to implement CMAC based on the insights obtained in the process is proposed. The… (More)

A multilayered neural network processor is used to control a given plant. Several learning architectures are proposed for training the neural controller to provide the appropriate inputs to the plant so that a desired response is obtained. A modified error-back propagation algorithm, based on propagation of the output error through the plant, is introduced.… (More)

- Mario Sznaier, Héctor Rotstein, Juanyu Bu, Athanasios Sideris
- IEEE Trans. Automat. Contr.
- 2000

- Athanasios Sideris, James E. Bobrow
- IEEE Trans. Automat. Contr.
- 2005

We develop a numerically efficient algorithm for computing controls for nonlinear systems that minimize a quadratic performance measure. We formulate the optimal control problem in discrete-time, but many continuous-time problems can be also solved after discretization. Our approach is similar to sequential quadratic programming for finite-dimensional… (More)

- Athanasios Sideris
- MCSS
- 1991

- Athanasios Sideris, Héctor Rotstein
- Automatica
- 1993

A sequential quadratic programming method is proposed for solving nonlinear optimal control problems subject to general path constraints including mixed state-control and state-only constraints. The proposed algorithm formulates linear quadratic optimal control subproblems with a solution that provides a descent direction for a non-differentiable exact… (More)

We propose a new algorithm for Support Vector Machine classification based on a geometric interpretation of the problem as finding the minimum distance between the polytopes defined by the points of the two classes. This geometric formulation applies to the hard margin, and the soft margin classification problem with quadratic violations. Our approach is… (More)

In this paper a state estimation technique is developed for sensing inclination angles using relatively low cost sensors. A low bandwidth tilt sensor is used along with an inaccurate rate gyro to obtain the measurement. The rate gyro has an inherent bias along with sensor noise. The tilt sensor uses an internal pendulum and therefore has its own slow… (More)