Carotti Elias S G, Shalchyan Vahid, Jensen Winnie, Farina Dario
Dipartimento di Automatica ed Informatica, Politecnico di Torino, Turin, Italy.
Med Biol Eng Comput. 2014 May;52(5):429-38. doi: 10.1007/s11517-014-1146-x. Epub 2014 Mar 18.
Intracortical signals are usually affected by high levels of noise [0 dB signal-to-noise ratio (SNR) is not uncommon] often due to magnetic or electrical coupling between surrounding sources and the recording system. Apart from hindering effective exploitation of the information content in the signals, noise also influences the bandwidth needed to transmit them, which is a problem especially when a large number of channels are to be recorded. In this paper, we propose a novel technique for joint denoising and compression of intracortical signals based on the minimum description length principle. This method was tested on both simulated and experimental signals, and the results showed that the proposed technique achieves improvements in SNR and compression ratios greater than alternative denoising/compression methods.
皮层内信号通常会受到高水平噪声的影响（0分贝信噪比并不罕见），这通常是由于周围源与记录系统之间的磁耦合或电耦合所致。除了阻碍对信号中信息内容的有效利用外，噪声还会影响传输这些信号所需的带宽，当要记录大量通道时，这尤其成问题。在本文中，我们基于最小描述长度原理提出了一种用于皮层内信号联合去噪和压缩的新技术。该方法在模拟信号和实验信号上均进行了测试，结果表明，所提出的技术在信噪比和压缩比方面比其他去噪/压缩方法有更大的提升。
