Ryan Mukai

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The use of radial basis function (RBF) networks and least squares algorithms for acquisition and fine tracking of NASA's 70-m-deep space network antennas is described and evaluated. We demonstrate that such a network, trained using the computationally efficient orthogonal least squares algorithm and working in conjunction with an array feed compensation(More)
The use of radial basis function networks for fine pointing NASA's 70-meter deep space network antennas is described and evaluated. We demonstrate that such a network, working in conjunction with the array feed compensation system, and trained using the computationally efficient orthogonal least-squares algorithm, can point a 70-meter deep space antenna(More)
  • R Mukai, V Vilnrotter, P Arabshahi, V Jamnejad
  • 2000
This article describes computationally intelligent neural-network and least-squares tracking algorithms for fine pointing NASA's 70-m Deep Space Network (DSN) antennas using the seven-channel Ka-band (32-GHz) array feed compensation system (AFCS). These algorithms process normalized inputs from the seven horns of the array in parallel and, hence, are less(More)
— A method for optimal adaptive setting of pulse-position-modulation pulse detection thresholds, which minimizes the total probability of error for the dynamically fading optical free space channel, is presented. The threshold's adaptive setting, in response to varying channel conditions, results in orders of magnitude improvement in probability of error,(More)
  • R Mukai, V Vilnrotter, P Arabshahi
  • 2000
1 This article describes computationally intelligent neural-network and least-squares algorithms for precise pointing of NASA's 70-meter Deep Space Network (DSN) antennas using the seven-channel Ka-band (32-GHz) array feed compensation system (AFCS). These algorithms process normalized data from the seven horns of the array in parallel and thus are more(More)
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