The Application Of Wiener Filtering

In our practical work, noises often disturb the collected signal, takeing troubles to us for the work. In this text, we can get rid of the noises disturbing our real signal through the function of filtering, making it attained the expectation signal we needed.Filtering issue is to dispose the signal that has been interfered with, to separate the anticipant signal. That is, disposing a series of measure data that have error and receiving the estimate value of anticipant data. In the few decades, filtering theory has already developed in a wide field, there are many different ways to introduce the content of it basing on different emphases. The dissertation is mainly introducing it and putting it into practical application.The dissertation designs a wiener filter basing upon minimum mean-square error. In fact, the essential of seeking minimum mean-square error is solving the Wiener-holf equation. And making the output signal and the expectation signal have the best approach at the least square. The dissertation introduces the basic principle of wiener filtering, discussing the solution of Wiener-holf equation at time-field and Z-field. And at the Z-field, having a discussion about white noise by Bode and Shannon. Taking the full single freedom pile foundation as an example, generally introduces the pile foundation detecting, adding noise then disposing it by wiener filtering, reveals the disposing results by picture and data.The results shows strong function which wiener filtering has at the aspect of disposing noise.