研华近日新推出采用了ARM／Xscale和Windows CE Embedded的VITA-350P移动数据终端和TREK-305R 5．7＂TFT车载显示面板2款产品。VITA-350P与TREK-305R完美搭配为车队所有者和驾驶员等提供可进行实时追踪的车队管理解决方案，同时还提供...研华近日新推出采用了ARM／Xscale和Windows CE Embedded的VITA-350P移动数据终端和TREK-305R 5．7＂TFT车载显示面板2款产品。VITA-350P与TREK-305R完美搭配为车队所有者和驾驶员等提供可进行实时追踪的车队管理解决方案，同时还提供了高效的调度导航与车辆数据采集系统。展开更多
The growing number of mobile users, as well as the diversification in types of services have resulted in increasing demands for wireless network bandwidth in recent years. Although evolving transmission techniques are...The growing number of mobile users, as well as the diversification in types of services have resulted in increasing demands for wireless network bandwidth in recent years. Although evolving transmission techniques are able to enlarge the network capacity to some degree, they still cannot satisfy the requirements of mobile users. Meanwhile, following Moore's Law, the data processing capabilities of mobile user terminals are continuously improving. In this paper, we explore possible methods of trading strong computational power at wireless terminals for transmission efficiency of communications. Taking the specific scenario of wireless video conversation, we propose a model-based video coding scheme by learning the structures in multimedia contents. Benefiting from both strong computing capability and pre-learned model priors, only low-dimensional parameters need to be transmitted; and the intact multimedia contents can also be reconstructed at the receivers in real-time. Experiment results indicate that, compared to conventional video codecs, the proposed scheme significantly reduces the data rate with the aid of computational capability at wireless terminals.展开更多
文摘研华近日新推出采用了ARM／Xscale和Windows CE Embedded的VITA-350P移动数据终端和TREK-305R 5．7＂TFT车载显示面板2款产品。VITA-350P与TREK-305R完美搭配为车队所有者和驾驶员等提供可进行实时追踪的车队管理解决方案，同时还提供了高效的调度导航与车辆数据采集系统。
基金supported by the National Basic Research Project of China (973) (2013CB329006)National Natural Science Foundation of China (NSFC, 61101071,61471220, 61021001)Tsinghua University Initiative Scientific Research Program
文摘The growing number of mobile users, as well as the diversification in types of services have resulted in increasing demands for wireless network bandwidth in recent years. Although evolving transmission techniques are able to enlarge the network capacity to some degree, they still cannot satisfy the requirements of mobile users. Meanwhile, following Moore's Law, the data processing capabilities of mobile user terminals are continuously improving. In this paper, we explore possible methods of trading strong computational power at wireless terminals for transmission efficiency of communications. Taking the specific scenario of wireless video conversation, we propose a model-based video coding scheme by learning the structures in multimedia contents. Benefiting from both strong computing capability and pre-learned model priors, only low-dimensional parameters need to be transmitted; and the intact multimedia contents can also be reconstructed at the receivers in real-time. Experiment results indicate that, compared to conventional video codecs, the proposed scheme significantly reduces the data rate with the aid of computational capability at wireless terminals.
