161 resultados para Coding Scheme


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This paper presents a new image data fusion scheme by combining median filtering with self-organizing feature map (SOFM) neural networks. The scheme consists of three steps: (1) pre-processing of the images, where weighted median filtering removes part of the noise components corrupting the image, (2) pixel clustering for each image using self-organizing feature map neural networks, and (3) fusion of the images obtained in Step (2), which suppresses the residual noise components and thus further improves the image quality. It proves that such a three-step combination offers an impressive effectiveness and performance improvement, which is confirmed by simulations involving three image sensors (each of which has a different noise structure).

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One major assumption in all orthogonal space-time block coding (O-STBC) schemes is that the channel remains static over the entire length of the codeword. However, time selective fading channels do exist, and in such case the conventional O-STBC detectors can suffer from a large error floor in the high signal-to-noise ratio (SNR) cases. This paper addresses such an issue by introducing a parallel interference cancellation (PIC) based detector for the Gi coded systems (i=3 and 4).

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All the orthogonal space-time block coding (O-STBC) schemes are based on the following assumption: the channel remains static over the entire length of the codeword. However, time selective fading channels do exist, and in many cases the conventional O-STBC detectors can suffer from a large error floor in the high signal-to-noise ratio (SNR) cases. This paper addresses such an issue by introducing a parallel interference cancellation (PIC) based detector for the Gi coded systems (i=3 and 4).

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The paper deals with an issue in space time block coding (STBC) design. It considers whether, over a time-selective channel, orthogonal STBC (O-STBC) or non-orthogonal STBC (NO-STBC) performs better. It is shown that, under time-selectiveness, once vehicle speed has risen above a certain value, NO-STBC always outperforms O-STBC across the whole SNR range. Also, considering that all existing NO-STBC schemes have been investigated under quasi-static channels only, a new simple receiver is derived for the NO-STBC system under time-selective channels.

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This paper proposes a three-shot improvement scheme for the hard-decision based method (HDM), an implementation solution for linear decorrelating detector (LDD) in asynchronous DS/CDMA systems. By taking advantage of the preceding (already reconstructed) bit and the matched filter output for the following two bits, the coupling between temporally adjacent bits (TABs), which always exists for asynchronous systems, is greatly suppressed and the performance of the original HDM is substantially improved. This new scheme requires no signaling overhead yet offers nearly the same performance as those more complicated methods. Also, it can easily accommodate the change in the number of active users in the channel, as no symbol/bit grouping is involved. Finally, the influence of synchronisation errors is investigated.

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We present a novel algorithm for joint state-parameter estimation using sequential three dimensional variational data assimilation (3D Var) and demonstrate its application in the context of morphodynamic modelling using an idealised two parameter 1D sediment transport model. The new scheme combines a static representation of the state background error covariances with a flow dependent approximation of the state-parameter cross-covariances. For the case presented here, this involves calculating a local finite difference approximation of the gradient of the model with respect to the parameters. The new method is easy to implement and computationally inexpensive to run. Experimental results are positive with the scheme able to recover the model parameters to a high level of accuracy. We expect that there is potential for successful application of this new methodology to larger, more realistic models with more complex parameterisations.

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A novel Neuropredictive Teleoperation (NPT) Scheme is presented. The design results from two key ideas: the exploitation of the measured or estimated neural input to the human arm or its electromyograph (EMG) as the system input and the employment of a predictor of the arm movement, based on this neural signal and an arm model, to compensate for time delays in the system. Although a multitude of such models, as well as measuring devices for the neural signals and the EMG, have been proposed, current telemanipulator research has only been considering highly simplified arm models. In the present design, the bilateral constraint that the master and slave are simultaneously compliant to each other's state (equal positions and forces) is abandoned, thus obtaining a simple to analyzesuccession of only locally controlled modules, and a robustness to time delays of up to 500 ms. The proposed designs were inspired by well established physiological evidence that the brain, rather than controlling the movement on-line, programs the arm with an action plan of a complete movement, which is then executed largely in open loop, regulated only by local reflex loops. As a model of the human arm the well-established Stark model is employed, whose mathematical representation is modified to make it suitable for an engineering application. The proposed scheme is however valid for any arm model. BIBO-stability and passivity results for a variety of local control laws are reported. Simulation results and comparisons with traditional designs also highlight the advantages of the proposed design.

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