Hello friends, I am new to signal processing and I am trying to achive deconvolution using FFT. I have an input step function u(t) applied to an impulse response given by . The output function is . I am trying to convolve g and u to get y as well as deconvolve y and g to get u. However, I quite cannot get the right answers. I understand that the deconvolution process is ill-posed and I have to use some kind of normalization process but I am lost. I also apply zero padding to twice the length of the input signals. Any sort of guidance will be appreciated.

After using deconvolution in the fourier domain:
Y = fft(y)
G = fft(g)
X = Y./G
x = ifft(X)
I am getting an output shown below:

Which is not the expected outcome. Can someone shead light on what is happening here? Thank you.Hello friends, I am new to signal processing and I am trying to achive deconvolution using FFT. I have an input step function u(t) applied to an impulse response given by . The output function is . I am trying to convolve g and u to get y as well as deconvolve y and g to get u. However, I quite cannot get the right answers. I understand that the deconvolution process is ill-posed and I have to use some kind of normalization process but I am lost. I also apply zero padding to twice the length of the input signals. Any sort of guidance will be appreciated.

After using deconvolution in the fourier domain:
Y = fft(y)
G = fft(g)
X = Y./G
x = ifft(X)
I am getting an output shown below:

Which is not the expected outcome. Can someone shead light on what is happening here? Thank you. Hello friends, I am new to signal processing and I am trying to achive deconvolution using FFT. I have an input step function u(t) applied to an impulse response given by . The output function is . I am trying to convolve g and u to get y as well as deconvolve y and g to get u. However, I quite cannot get the right answers. I understand that the deconvolution process is ill-posed and I have to use some kind of normalization process but I am lost. I also apply zero padding to twice the length of the input signals. Any sort of guidance will be appreciated.

After using deconvolution in the fourier domain:
Y = fft(y)
G = fft(g)
X = Y./G
x = ifft(X)
I am getting an output shown below:

Which is not the expected outcome. Can someone shead light on what is happening here? Thank you. deconvolution, fft, inverse problem MATLAB Answers — New Questions

​