With the rapid development of wireless sensor networks（ WSNs）

processing

storing and transmitting huge amounts of data for traditional ADC at high speed and storage communication equipment has brought great pressure. Due to the time of sensory data from the sensor node has a correlation

put forward sampling and compression method based on compressed sensing theory

it breaks the limitation of traditional Nyquist sampling theorem

in the front just is far lower than the Nyquist sampling frequency sampling signal can complete the accurate reconstruction of the original signal

and construct model analog-to-information convertor（ AIC）

based on compression perception using platform of Matlab simulation experiment is carried out

the results show that the model can accurately reconstruct sparse signal using less observations

and the reconstruction precision is related to the observed number M and the sparse degree K.