基于Gabor原子的活立木茎体水分信号MP分解与重构

MP decomposition and reconstruction of living tree stem moisture signals based on Gabor atoms

针对活立木茎体水分时域信号呈现的非平稳、信息冗余特性,提出了一种基于Gabor原子的活立木茎体水分信号MP分解与重构方法。试验结果表明活立木茎体水分信号可以用Gabor原子库稀疏表示,靠前的原子反映信号的主要特征,靠后的原子反映信号的细微特征,原子数越多,稀疏信号越能更好地描述原始时域信号的特征。稀疏信号对比于原始时域信号,数据量明显减少,避免了信息冗余,达到了数据压缩的目的,为大量数据的存储节省了物理空间。在Gabor原子库过冗余的情况下,稀疏信号可以高质量的重构出原始时域信号,在主要特征数据点处重构误差较小,在细微特征数据点处重构误差较大。

Considering the nonstationarity and information redundancy of living tree stem moisture signals in time domain,an approach of MP decomposition and reconstruction of living tree stem moisture signals based on Gabor atoms was presented.The experimental results showed that living tree stem moisture signals can be represented sparsely by Gabor atom library.The front of atoms reflected the main features of signal and the back of atoms reflected the subtle features of signal.The more the number of atoms was,the more the sparse signal can better represent the features of original time-domain signal.Compared with the original signal in time domain,the sparse signal had many advantages.Firstly,the length of sparse signal was reduced significantly.Secondly,the sparse signal can avoid information redundancy.So the approach of representing signal sparsely can achieve the purpose of data compression and save physical space to store a large amount of data.Under the condition of Gabor atom library being redundant,original time-domain signal can be constructed with high quality from the sparse signal.And reconstructive errors at the main feature points were larger than it at the subtle feature points.