# LMS Algorithm: How to Define the Desired Signal

I am working on LMS algorithm,i am not getting exactly how we get desired response of the filter that is compared with the estimated output

• As for as I know, the desired signal for the LMS algorithm depends on application type. One example is given by the user (Matt L.) who commented above. The LMS algorithm find an iterative solution to the Wiener-Hopf equation. The LMS algorithm, may assume the model $y(n)=d(n)+w(n)$ for the (received or measured) data, where $d(n)$ is the desired signal and $w(n)$ is a random noise process. For what application you are using the LMS algorithm? Filtering, prediction, deconvolution or extrapolation? – Oliver Apr 8 '14 at 12:25
• im using it for filtering(isi removal or for channel eualization) – sumaira Apr 9 '14 at 6:15
• Please refer to the text book - "Statistical Digital Signal Processing and Modeling" by Monson H. Hayes. Pages 530-534. They contain what exactly you need . Also, refer page 506. I hope this helps you. – Oliver Apr 9 '14 at 6:39