After analyzing, the windowing method Frequency sampling method was analyzed for filter design using Scilab. Here, DFT is used,as frequency response at discrete values of frequency is obtained. The output h[n] is obtained by performing inverse-DFT. As discrete values of the frequency response, it can be considered that the response is sampled,hence the name FSM. As DFT involves summation, it can be easily computed compared to integration in IDTFT in windowing method. The filter order obtained using both methods is the same. h[n] obtained is symmetric.
The most easiest way of filter design.
ReplyDeleteIt's considered simple.
DeleteComplete info is shared properly.
ReplyDeleteRefer TI's documentation.
DeleteFSM implementation is faster!!
ReplyDeleteTrue. Less computations are involved.
DeleteFsm is easy to implement
ReplyDeleteTrue.
DeleteHowever, has time aliasing effects
ReplyDeleteNyquist criteria must be satisfied.
DeleteIt requires less computations.
ReplyDeleteTrue.
Deletegood.
ReplyDeleteThanks.
DeleteFSM requires lesser number of input parameters
ReplyDeleteThe computations are less.
DeleteOptimization is easier in FSM as it is simpler
ReplyDeleteTrue.
DeleteYes. They can be implemented using software.
ReplyDelete