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Fig. 9.9. (left) Eye tracking of a fixed target in a noisy environment of 0dB SNR: "a" respresents fixed target, "b" represents target tracking using RQNN model and "c" represents target tracking using a Kalman filter. The noise envelope is represented by the curve "d"; (right) The snapshots of the wave packets at different instances corresponding to the marker points (1,2,3) as shown in the left figure. The solid line represent the initial wave packet assigned to the Schrodinger wave equation a continuous fashion. This is very clearly understood from the tracking error in Fig. 9.10.

The other interesting aspect of the results is the movement of wave packets. It is observed that these wave packets move in discrete steps, i. e. the movement is not continuous. In Fig. 9.9 (right), snapshots of wave packets

Fig. 9.10. The continuous line represents the tracking error using RQNN model, while the broken line represents the tracking error using a Kalman filter t

Fig. 9.10. The continuous line represents the tracking error using RQNN model, while the broken line represents the tracking error using a Kalman filter

9 Recurrent Quantum Neural Network and its Applications 345 0.4

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