论文标题
评估压缩传感技术效率的指标
Metrics for Evaluating the Efficiency of Compressing Sensing Techniques
论文作者
论文摘要
由于其能够加快数据获取的能力，因此，压缩感知在许多领域都受到了许多领域的兴趣。当信号在某些域中稀疏时，该框架允许快速的信号采集和压缩。它仅使用几个样品从高维稀疏信号中提取主要信息，然后从少数测量值中恢复稀疏信号。在使用压缩感应方面，有两个要点要考虑。第一个是如何设计线性测量矩阵，以确保压缩感应达到应用程序的目标。第二个是如何从几个测量值中恢复稀疏信号。进行压缩感应需要分析和研究测量矩阵和恢复算法的效率。迄今为止，构建明确的测量矩阵和开发有效的恢复算法仍然是应用程序中的挑战。因此，本文描述了评估压缩感测技术的性能的指标。
Compressive sensing has been receiving a great deal of interest from researchers in many areas because of its ability in speeding up data acquisition. This framework allows fast signal acquisition and compression when signals are sparse in some domains. It extracts the main information from high dimensional sparse signals using only a few samples, then the sparse signals are recovered from the few measurements. There are two main points to consider when it comes to using compressive sensing. The first one is how to design the linear measurement matrix to ensure that the compressive sensing is meeting the objectives of the application. The second is how to recover the sparse signal from few measurements. Performing compressive sensing requires analyzing and investigating the efficiency of the measurement matrix and the recovery algorithm. To date, constructing explicit measurement matrices and developing efficient recovery algorithms are still open challenges in applications. Thus, this paper describes metrics to evaluate the performance of compressive sensing techniques.
