基于稀疏快速傅里叶变换的信号压缩处理

Signal compression processing based on sparse fast Fourier transform

随着数据采集能力和采样频率的不断提高,采用传统的奈奎斯特采样定理会获得海量的数据,这给信号的存储和传递带来了极大挑战。提出基于稀疏快速傅里叶变换的信号压缩方法,利用信号在频域的稀疏性,压缩信号所需的存储空间,在保证拥有足够小的误码率的前提下,以高概率重构原始信号。

With the continuous improvement of data collection capabilities and the sampling frequency, the traditional Nyquist sampling theorem would get massive data, which gives the major challenge of signal storage and transmission. In this paper, we propose a new signal compression method based on fast Fourier transform. Using the sparsity of the signal in the frequency domain, it reduces the storage space of the signal. It reconstructs the original signal with high probability on a basis of small error rate.