This short paper is based on Chung et al. (2010), where the cosine series representation (CSR) is used in modeling the shape of white matter fiber tracts in diffusion tensor imaging(DTI) and Wang et al. (2018), where the method is used to denoise EEG. The proposed explicit analytic approach offers far superior flexibility in statistical modeling compared to the usual implicit Fourier transform methods such as the discrete cosine transforms often used in signal processing. The MATLAB codes and sample data can be obtained from http://brainimaging.waisman.wisc.edu/~chung/tracts.
翻译:本简短文件以Chung等人(2010年)为基础,在该文件中,共弦代号(CSR)用于模拟白物质纤维在扩散高温成像中的形状(DTI)和Wang等人(2018年)的形状,该方法用于隐蔽 EEG。提议的明确分析方法在统计建模方面提供了比通常的隐含Fourier变异方法(如在信号处理中经常使用的离散共弦变换)更大的灵活性。MATLAB代码和样本数据可从http://brainimaging.waisman.wisc.edu/~chung/traps获得。