Considering all possible candidate motion vectors in a given search area and calculating a distortion measure at every search position, as with the full-search block-matching motion estimation algorithm (FSBME), place...
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Considering all possible candidate motion vectors in a given search area and calculating a distortion measure at every search position, as with the full-search block-matching motion estimation algorithm (FSBME), places a prohibitively high computational burden on the video encoder, making it unsuitable for real-time/portable video applications. To reduce computationalcomplexity while maintaining accuracy, a new version of the reduced-bit, sum of absolute difference (RBSAD) algorithm is presented, which allows for optional correction to full resolution (FSBME) when appropriate. Analysis of a number of video sequence shows that this correction is required for blocks for which there is little motion between frames.
The area of Layered Space-Time (LST) systems has received enormous attention recently as they can provide a roughly linear increase in data rate by using Multiple Transmit and Receive antennas. The optimal detection s...
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ISBN:
(纸本)0780382196
The area of Layered Space-Time (LST) systems has received enormous attention recently as they can provide a roughly linear increase in data rate by using Multiple Transmit and Receive antennas. The optimal detection strategy for a LST receiver is to perform a Maximum-Likelihood (ML) search over all possible transmitted symbol combinations has an exponential complexity when the constellation size of number of transmit antennas increase. While sub-optimal decoders, such as VBLAST, provide linear decoding only where the number of receive antennas is at least equal to the number of transmit antennas. The decoding scheme proposed in this paper, called Asterism decoding, looks for a more efficient way of finding the ML solution by first considering the case of multiple transmit antennas and a single receive antenna. The decoder is then extended to achieve ML like performance for any number of receive antennas. It further shows that Asterism decoding has at least an approximate order of magnitude reduction in computationalcomplexity when compared to ML decoding. Asterism decoding is the first lower complexity decoder that achieves ML-like performance for systems where the number of receive antennas is less than the number of transmit antennas without the additional use of error coding.
A parallelised max-Log-MAP model (P-max-Log-MAP) that exploits the sub-word parallelism and very long instruction word architecture of a microprocessor or a digital signal processor (DSP) is presented. The proposed mo...
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A parallelised max-Log-MAP model (P-max-Log-MAP) that exploits the sub-word parallelism and very long instruction word architecture of a microprocessor or a digital signal processor (DSP) is presented. The proposed model reduces considerably the computationalcomplexity of the max-Log-MAP algorithm;and therefore facilitates easy implementation.
A method to significantly reduce the computationalcomplexity of a serial interference cancellation scheme for CDMA receivers, while maintaining the receiver performance, is presented. The reduced complexity is achiev...
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A method to significantly reduce the computationalcomplexity of a serial interference cancellation scheme for CDMA receivers, while maintaining the receiver performance, is presented. The reduced complexity is achieved by accelerating the convergence rate of the algorithm with a preconditioning technique.
Based on a study of the motion vector (MV) obtained by the Full Search algorithm among several test sequences, we found that the prediction process for motion estimation in many existing algorithms are not optimal. We...
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ISBN:
(纸本)0780374029
Based on a study of the motion vector (MV) obtained by the Full Search algorithm among several test sequences, we found that the prediction process for motion estimation in many existing algorithms are not optimal. We optimize the prediction process by classifying the blocks into four different classes based on a newly proposed three-dimensional reference MV. Different search patterns and strategies are used for each class. The proposed algorithm can improve computation requirement as high as 43.9% than the diamond search algorithm.
An approximate maximum likelihood method for joint estimation of time delays and directions-of-arrival for direct-sequence code-devision multiple-access systems over multipath Rayleigh fading channels is presented. To...
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An approximate maximum likelihood method for joint estimation of time delays and directions-of-arrival for direct-sequence code-devision multiple-access systems over multipath Rayleigh fading channels is presented. To reduce the computationalcomplexity, the multi-dimensional maximisation problem is transformed into two simple one-dimensional maximisation problems using an iterative scheme. To illustrate the performance, simulation results are compared with Cramer-Rao bounds.
A local extended Kalman filter training and pruning approach is proposed to train feedforvard networks with the goal of reducing the computationalcomplexity and storage requirement in large-scale practical problems. ...
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A local extended Kalman filter training and pruning approach is proposed to train feedforvard networks with the goal of reducing the computationalcomplexity and storage requirement in large-scale practical problems. The performance of the proposed algorithm is demonstrated for the problem of handwritten digit recognition.
An improved projection transformation method for enhancing the performance of the linearly constrained minimum variance beamformer is presented in this paper. The novel algorithm uses a projection operator, which is t...
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ISBN:
(纸本)0780370007
An improved projection transformation method for enhancing the performance of the linearly constrained minimum variance beamformer is presented in this paper. The novel algorithm uses a projection operator, which is the basis vectors for the estimated signal-plus-interference subspace obtained by searching for it in the array manifold space by means of priori knowledge. The new algorithm can further reduce the computationalcomplexity and eliminate the signal cancellation, when a desired signal is contained in the correlation matrix. Moreover, the new method has good beam pattern with lower sidelobe level and faster convergence speed in the case that there exist amplitude and phase errors and/or colored noise. The advantages are confirmed by computer simulations.
A new group tracking algorithm is developed. The algorithm is capable of initiating groups, accounting for merging or splitting groups, and presenting group centroids dynamic state. Group initiation and merging proced...
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ISBN:
(纸本)0780370007
A new group tracking algorithm is developed. The algorithm is capable of initiating groups, accounting for merging or splitting groups, and presenting group centroids dynamic state. Group initiation and merging procedures are based on multiple hypothesis tracking (MHT), and targets deviating from the group are caught by the MHT again. Thus, computational resources are reduced and the performance is improved. Group maintenance under different situations is discussed in detail.
It is known that the convergence rate of the LMS algorithm is slow, especially when the channel has severe spectral nulls. The convergence rate of RLS is fast, but the computationalcomplexity is high. A hierarchical ...
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It is known that the convergence rate of the LMS algorithm is slow, especially when the channel has severe spectral nulls. The convergence rate of RLS is fast, but the computationalcomplexity is high. A hierarchical RLS algorithm is proposed to reduce the computationalcomplexity and increase the convergence rate of the RLS.
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