ADI公司的ADAQ4003μModule®精密数据采集(DAQ)信号链解决方案,可降低精密测量系统的开发周期,优化元件选择和布局.ADAQ4003能保证18位无失码,吞吐速率为2 MSPS,无流水线延迟.动态功耗调节,2 MSPS时待确定功耗为m W,积分非线性为&#...ADI公司的ADAQ4003μModule®精密数据采集(DAQ)信号链解决方案,可降低精密测量系统的开发周期,优化元件选择和布局.ADAQ4003能保证18位无失码,吞吐速率为2 MSPS,无流水线延迟.动态功耗调节,2 MSPS时待确定功耗为m W,积分非线性为±0.5 LSB,1 k Hz时SINAD为100 d B(增益=0.9),1 k Hz时的总谐波失真为-120 d B,100k Hz时为-100 d B.ADAQ4003具有信号缩放功能的集成式全差分ADC驱动器.展开更多
In secure multicast, one of the challenging problems is the authentication of multicast packets. This paper presents a novel scheme to address this problem, which combines ideas in both the hash tree schemes and the h...In secure multicast, one of the challenging problems is the authentication of multicast packets. This paper presents a novel scheme to address this problem, which combines ideas in both the hash tree schemes and the hash chain schemes. In this scheme, a group of packets is partitioned into equal-sized subgroups. Then a Merkle hash tree is built for each subgroup of packets, and the hash value of every root is appended to preceding packets to form hash chains. Its performance is analyzed and simulated using Biased Coin Toss loss model and 2-state Markov Chain loss model, respectively. Compared with the original hash chain schemes, results show that this scheme is much more efficient in term of communication overhead.展开更多
文摘ADI公司的ADAQ4003μModule®精密数据采集(DAQ)信号链解决方案,可降低精密测量系统的开发周期,优化元件选择和布局.ADAQ4003能保证18位无失码,吞吐速率为2 MSPS,无流水线延迟.动态功耗调节,2 MSPS时待确定功耗为m W,积分非线性为±0.5 LSB,1 k Hz时SINAD为100 d B(增益=0.9),1 k Hz时的总谐波失真为-120 d B,100k Hz时为-100 d B.ADAQ4003具有信号缩放功能的集成式全差分ADC驱动器.
基金Supported by the Natural Science Foundation of China (No. 60173066)
文摘In secure multicast, one of the challenging problems is the authentication of multicast packets. This paper presents a novel scheme to address this problem, which combines ideas in both the hash tree schemes and the hash chain schemes. In this scheme, a group of packets is partitioned into equal-sized subgroups. Then a Merkle hash tree is built for each subgroup of packets, and the hash value of every root is appended to preceding packets to form hash chains. Its performance is analyzed and simulated using Biased Coin Toss loss model and 2-state Markov Chain loss model, respectively. Compared with the original hash chain schemes, results show that this scheme is much more efficient in term of communication overhead.
