By mcans of stable attractors of discret Hopfield neural network (DHNN) , anew class of nonlinear error control codes is sugsested and some relativetheorems are presented. A kind of single error control codes is also ...By mcans of stable attractors of discret Hopfield neural network (DHNN) , anew class of nonlinear error control codes is sugsested and some relativetheorems are presented. A kind of single error control codes is also given forillustrating this new approach.展开更多
Packet loss protection method based on picture level adaptive frame /field coding (PAFF)was presented. Firstly,the end-to-end rate-distortion analysis for PAFF on the current frame was performed. Secondly,in order to ...Packet loss protection method based on picture level adaptive frame /field coding (PAFF)was presented. Firstly,the end-to-end rate-distortion analysis for PAFF on the current frame was performed. Secondly,in order to evaluate the severity of error propagation in the following frames,the error propagation intensity and human visual quality sensitivity of different areas were taken into consideration. It was followed by the quantification of relative importance. Finally,the proper coding mode was chosen utilizing an unequal comparison procedure. The simulation results show that the proposed method can improve peak signal-to-noise ratio (PSNR) up to 0. 9 dB and 1. 6 dB comparing with the field only and the dispersed flexible macro-block ordering (FMO)only methods respectively.展开更多
In this paper we introduce a framework for using quality as an incentive to promote proper application level congestion control. Through integrating a joint-source channel coder and feedback-based congestion control s...In this paper we introduce a framework for using quality as an incentive to promote proper application level congestion control. Through integrating a joint-source channel coder and feedback-based congestion control scheme, we are able to construct accurate and efficient quality incentives. The framework is applicable in all network architectures where end-to-end congestion control may be used, and is as such not specific to either best-effort or traffic class-based architectures. The concept is presented along with preliminary simulations that highlight the resulting rate control accuracy. We also discuss how to implement some well-known congestion control schemes within our framework.展开更多
文摘By mcans of stable attractors of discret Hopfield neural network (DHNN) , anew class of nonlinear error control codes is sugsested and some relativetheorems are presented. A kind of single error control codes is also given forillustrating this new approach.
基金National Natural Science Foundation of China(No.40927001)the Project of Key Scientific and Technological Innovation Team of Zhejiang Province,China(No.2011R09021-06)the Fundamental Research Funds for the Central Universities,China
文摘Packet loss protection method based on picture level adaptive frame /field coding (PAFF)was presented. Firstly,the end-to-end rate-distortion analysis for PAFF on the current frame was performed. Secondly,in order to evaluate the severity of error propagation in the following frames,the error propagation intensity and human visual quality sensitivity of different areas were taken into consideration. It was followed by the quantification of relative importance. Finally,the proper coding mode was chosen utilizing an unequal comparison procedure. The simulation results show that the proposed method can improve peak signal-to-noise ratio (PSNR) up to 0. 9 dB and 1. 6 dB comparing with the field only and the dispersed flexible macro-block ordering (FMO)only methods respectively.
基金Project supported by the Research Council of Norway, Norwegian University of Science and Technology (NTNU) and the Norwegian Resarch Network (UNINETT)
文摘In this paper we introduce a framework for using quality as an incentive to promote proper application level congestion control. Through integrating a joint-source channel coder and feedback-based congestion control scheme, we are able to construct accurate and efficient quality incentives. The framework is applicable in all network architectures where end-to-end congestion control may be used, and is as such not specific to either best-effort or traffic class-based architectures. The concept is presented along with preliminary simulations that highlight the resulting rate control accuracy. We also discuss how to implement some well-known congestion control schemes within our framework.
