Overlap Add Method and Overlap Save Method
This was 4th experiment. In this experiment we perform filtering of Long Data Sequences using OAM and OSM.
To perform a c program was written and executed and output was found as desired.
Overlap Add Method
In this method input signal x(n) is decomposed into no. of L point sequences using formula N=L+M-1, where M is length of h(n) and N is assumed to be Radix2 value. Then we find linear convolution between every decomposed signal and h(n) using FFT algorithm. The Inverse FFT is then performed on all output signals and the outputs are added to get final result.
Overlap Save Method
In this method input signal x(n) is again decomposed into L point sequences using formula N>=L+M-1, where M is length of h(n) and N is assumed to be Radix2 value. Here every decomposed signal is begins with (N-L) last values of previous signal. Then we find linear convolution between every decomposed signal and h(n) using FFT algorithm. The Inverse FFT is then performed on all output signals. Now we discard first (N-L) values of every output signal and save the remaining values. The final output signal is obtained by concatenating all the saved values.
These methods are used for Filtering of long finite data sequences and hence for FIR filter design.
To perform a c program was written and executed and output was found as desired.
Overlap Add Method
In this method input signal x(n) is decomposed into no. of L point sequences using formula N=L+M-1, where M is length of h(n) and N is assumed to be Radix2 value. Then we find linear convolution between every decomposed signal and h(n) using FFT algorithm. The Inverse FFT is then performed on all output signals and the outputs are added to get final result.
Overlap Save Method
In this method input signal x(n) is again decomposed into L point sequences using formula N>=L+M-1, where M is length of h(n) and N is assumed to be Radix2 value. Here every decomposed signal is begins with (N-L) last values of previous signal. Then we find linear convolution between every decomposed signal and h(n) using FFT algorithm. The Inverse FFT is then performed on all output signals. Now we discard first (N-L) values of every output signal and save the remaining values. The final output signal is obtained by concatenating all the saved values.
These methods are used for Filtering of long finite data sequences and hence for FIR filter design.
Very informative..! Normally OAM method is preferred..
ReplyDeleteCan you explain me how OAM is prefferred over OSM. Because generally Both equal.
DeleteOAM and OSM are done by using time domain method in theory as it is very difficult to calculate FFT of such a long data sequence
ReplyDeleteIf input signal is Not a longer sequence then we prefer FFT algorithm for practical application unless it is a real time sequence.
DeleteThe applications of DFT and FFT methods are well explained!
ReplyDeleteIn case of real time applications in DSP the OAM or OSM for convolution of long data sequences .
ReplyDeleteVery lucid explanation of this techniques.It would be better if you could have posted the step by step algorithm.
ReplyDeleteThe step by step procedure of the methods is explained in the blog.
Delete