• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.343-355
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• 2007

Using the modulus of smoothness ${\omega}^2_{{\varphi}^{\lambda}(f,t)_{\omega}$ Stechkin-Marchaud-Type inequalities with Jacobi weights of Bernstein Operators is established.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.4
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• pp.295-300
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• 1990

Inverse kinematic problem is a crucial point for robot manipulator control. In this paper, to implement the Jacobian control technique we used the Hopfield, Tank's neural network. The states of neurons represent joint velocities, and the connection weights are determined from the current value of the Jacobian matirx. The network energy function is constructed so that its minimum corresponds to the minimum least square error. At each sampling time, connection weights and neuron states are updated according to current joint positon. Inverse kinematic solution to the planar redundant manipulator is solved by computer simulation.