DSPP experiment 1

Our first experiment was based on linear convolution ,circular convolution and linear convolution using circular convolution.
1.In linear convolution ,the length of the output signal comes out to be L+M-1,where L and M are lengths of two signals.
2.Whereas in circular convolution,we get aliased output.In circular convolution we get the overlapped values with reference to result of linear convolution.
3.and in linear convolution using circular convolution ,
we select N>=L+M-1.

Comments

  1. Unknown25 April 2017 at 22:47

    Circular convolution gives aliased output

    ReplyDelete
  2. Unknown25 April 2017 at 22:49

    Zero padding is used in circular convolution

    ReplyDelete
  3. Unknown25 April 2017 at 22:50

    Linear convolution is easy to compute in time domain

    ReplyDelete
  4. Unknown28 April 2017 at 05:47

    Convolution is used to find the output.

    ReplyDelete
  5. Unknown28 April 2017 at 06:09

    The lengths of input signals are used to calculate the length of output signal

    ReplyDelete
  6. Chaitanya S28 April 2017 at 07:02

    Correlation gives degree of similarity of two signals

    ReplyDelete
  7. Unknown28 April 2017 at 07:27

    When going for circular convolution always select N = Max(L,M)

    ReplyDelete

Post a Comment

Popular posts from this blog

FIR filter design using the FSM approach.

In this the flow of the parameter calculation was kept the same as was for the window function.Nevertheless ,an added parameter called H(k) was calculated which o is the notation for DFT result.The length of this result was obtained from the Order of the filter which was given.Further omega was taken to be (2πk/N) where N was the order.One other ,slightly difficult task was plotting the realisation diagram.Ofcourse we didn't do this but the function was separated in its cascaded form for getting h(n) by sampling.The frequency sampling approach allows is to design the filter for both -std.frequency responses and arbitrary responses.Its applications include biomedical signal processing, compression etc. The main idea of the frequency sampling design method is that a desired frequency response can be approximated by sampling it of N evenly spaced points and then obtaining an interpolated frequency response that passes through the frequency sample.
Read more

Butterworth Filter Design

In this experiment we designed an IIR Filter namely Butterworth Filter.The Passband and Stop Band Attenuation were kept constant at 45db and 3db respectively.The code for the order and the normalised filter was typed according to the theory.BLT method was used for getting the exact transfer function.Further,the graph observed was minimally flat graph with no ripple in Pass band and Stop Band.Due to its maximum flat pass band nature it is used as anti-aliasing filter in data converter applications.
Read more

Chebyshev Filter Design

The aim of this experiment was to design a Chebyshev Filter.The formulae were completely different from those of Butterworth Filter.The flow followed was the same ,i.e the order and the normalised function was calculated first followed by the transfer function using BLT approach.Two types of Chebyshev Filters namely 1 and 2 were studied.The first one had ripple in Passband and the second one had ripple in Stopband.The order of the filter could be calculated from the graph by counting the number of ripples in either Stop Band or Pass Band which was interesting.It is used where the frequency content is more important than having a constant Amplitude.It is widely used in RF Applications because of its Steep Roll off.
Read more