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A new AI-based technology developed by Cornell researchers will help gain new insights into how our brains respond to external stimuli.
As smartphones, tablets, smart TVs and other smart devices become more prevalent in our lives, computer scientists have raised concerns that these network-enabled devices, if not properly secured, cou...
With the exponential growth of multimedia content in recent years (in particular, real-time video for entertainment) and the availability of the same content at multiple locations (e.g., the same vide...
Recent research on learning from selfobservation through video has shown positive effects on skill acquisition in various domains such as sports (Horn, Williams, & Scott, 2002; Guadagnoli, Holcomb, & ...
Music by women composers; women in music and technology; women in love.
Schenkerian music theory supposes that Western tonal compositions can be viewed as hierarchies of musical objects. The process of Schenkerian analysis reveals this hierarchy by identifying connections...
In passive coherent locators (PCL) systems, noise and the precision of direction of arrival (DOA) estimation are key issues. This paper addresses the implementation of high-resolution DOA estimation m...
在介绍正交频分复用(OFDM)技术基本原理和基本接收模型的基础上,提出将空间谱估计中的多重信号分类(MUSIC)算法应用到OFDM系统参数盲估计中。经过MATLAB实验仿真表明,在没有信号先验知识的情况下,此算法对信噪比较低的仿真OFDM信号和实际802.11a信号均能有效估计出其子载波个数和发射端作傅立叶反变换的点数。
介绍了一种基于分布式并行处理平台的并行MUSIC实现方法。在实现过程中,针对MUSIC算法运算量大难以实时实现的特点,采取了有效减少计算量的措施。并根据MUSIC算法各个子任务的不平衡性,提出了一种基于软件流水的并行任务划分方法。经仿真试验证明,经过上述并行处理后可有效加快算法的完成时间,在工程实践中具有广泛的实际意义。

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