Nidal Shakarneh

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Genetic Algorithm (GA) is a powerful technique for solving optimization problems. It follows the idea of survival of the fittest Better and better solutions evolve from previous generations until a near optimal solution is obtained. GA uses the main three operations, the selection, crossover and mutation to produce new generations from the old ones. GA has(More)
When multiple correlated data channels are simultaneously processed, multichannel-autoregressive (M-AR) processes may be combined with optimal filtering such as Kalman or H∞ for prediction or estimation from noisy observations. However, the estimation of the M-AR parameters from noisy observations is a key issue to be addressed. Off-line or iterative(More)
When multiple correlated data channels are simultaneously processed, multichannel-autoregressive (M-AR) processes may be combined with optimal filtering such as Kalman or H<sub>&#x221E;</sub> for prediction or estimation from noisy observations. However, the estimation of the M-AR parameters from noisy observations is a key issue to be addressed. Off-line(More)
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