deconvolution problem

Started by sofiyya in comp.dsp10 years ago 1 reply

Hi, I have a problem with vector deconvolution. This is what I do in Matlab: > > vect1=[1 2 3 4 5 6 7 8 9]; > > vect2=[1 2 3 4 0 0 0 0 0...

Hi, I have a problem with vector deconvolution. This is what I do in Matlab: > > vect1=[1 2 3 4 5 6 7 8 9]; > > vect2=[1 2 3 4 0 0 0 0 0 0 0 0 0 0]; %I want to find w with conv(w,vect1)=vect2 > > Lx=length(vect2)-length(vect1)+1; > > Lx2=pow2(nextpow2(Lx)); > > VECT1=fft(vect1,Lx2); > > VECT2=fft(vect2,Lx2); > > W=VECT2 ./ VECT1; > > w=real(ifft(W,Lx2)); > > w=w(1:1:Lx); > > w=w/max(abs(w));


deconvolution problem

Started by sofiyya in comp.dsp10 years ago 23 replies

Hi, I have a problem with vector deconvolution. This is what I do in Matlab: > > vect1=[1 2 3 4 5 6 7 8 9]; > > vect2=[1 2 3 4 0 0 0 0 0...

Hi, I have a problem with vector deconvolution. This is what I do in Matlab: > > vect1=[1 2 3 4 5 6 7 8 9]; > > vect2=[1 2 3 4 0 0 0 0 0 0 0 0 0 0]; %I want to find w with conv(w,vect1)=vect2 > > Lx=length(vect2)-length(vect1)+1; > > Lx2=pow2(nextpow2(Lx)); > > VECT1=fft(vect1,Lx2); > > VECT2=fft(vect2,Lx2); > > W=VECT2 ./ VECT1; > > w=real(ifft(W,Lx2)); > > w=w(1:1:Lx); > > w=w/max(abs(w));


Design of a deconvolution filter

Started by axr0284 in comp.dsp13 years ago 3 replies

Hi, I am really new to this so bear with me. I got a homework assignment for a course called analytical topics and I was wondering if anybody...

Hi, I am really new to this so bear with me. I got a homework assignment for a course called analytical topics and I was wondering if anybody could help me figure it out. I don't need a complete answer but just some pointers of where to begin with this problem and how to proceed. Thank you very much for any information. The setup is as follows: I am given an fir filter: y(k)=sum[u(k-i)h(k)] ...


Deconvolution

Started by HardySpicer in comp.dsp10 years ago 6 replies

If I have a random signal u(k) and a (known) transfer function H then y(k)=Hu(k) and if I know H and H is minimum phase then I ca neasily find...

If I have a random signal u(k) and a (known) transfer function H then y(k)=Hu(k) and if I know H and H is minimum phase then I ca neasily find u(k). Suppose H is nonminimum phase eg y(k)=u(k)-2u(k-1) how to get at u(k)? Can I run time backwards in some way so the H is stable in reverse time? hardy


deconvolution in time?

Started by Julian Stoev in comp.dsp14 years ago 21 replies

Hello! I have a output signal y(k) and a plant P(z). The signal y(k) contains some noise and I know the PSD of the noise. But lets assume that...

Hello! I have a output signal y(k) and a plant P(z). The signal y(k) contains some noise and I know the PSD of the noise. But lets assume that for now that the noise is qhite and the system looks like this: Y(z)=U(z)P(z)+E(z) u(k) y(k) ----------> [P(z)]--> [+]---> | e(k) | -------| I want to restore the sig


Prewhitening....how to explain?

Started by Vicki in comp.dsp14 years ago 11 replies

Hi All, Is there a book or source that explains what prewhitening is, in relatively simple terms? Or would any of you like to explain it to...

Hi All, Is there a book or source that explains what prewhitening is, in relatively simple terms? Or would any of you like to explain it to me, please? I have a blood flow signal and I want to prewhiten it and then do some blind deconvolution on it to see what happens. As the prewhitener it has been suggested to use a predictor as the signals I have are quite short. (Some form of stocha...


Deconvolution by Fourier method

Started by aries44 in comp.dsp14 years ago 5 replies

In order to convolve two functions 'a' and 'b', we can take their Fourier Transform(FT) and multiply them in Fourier domain i.e. C= FT(a) *...

In order to convolve two functions 'a' and 'b', we can take their Fourier Transform(FT) and multiply them in Fourier domain i.e. C= FT(a) * FT(b) c = IFT(C) and then Inverse Ft(IFT) of 'C' gives us the convolution of 'a' and 'b'. Now if we want to deconvolve 'a' from 'c' to get 'b' we can do B = FT(c)/FT(a) b = IFT(B) Now if 'a' is a square wave i face the problem of 'DIVIDE by ZERO', a...


Deconvolution of two gamma variates

Started by PaulPaul in comp.dsp13 years ago 1 reply

Hi! I'm busy with a project to determine cerebral blood flow using MRI. At two places in the brain the concentration of a contrast solution...

Hi! I'm busy with a project to determine cerebral blood flow using MRI. At two places in the brain the concentration of a contrast solution is measured every 1 second (or so.) The points are then fitted to a gamma variate of the form: f(t) = a (t-to)^b exp[ -(t-t0)/c ] for t=> t0 f(t) = 0 t


how to minimize ringing

Started by Keren in comp.dsp9 years ago 4 replies

Hello, I am trying to restore a one dimentional signal using wiener deconvolution with a PSF. Because it's important for me to restore sharpness,...

Hello, I am trying to restore a one dimentional signal using wiener deconvolution with a PSF. Because it's important for me to restore sharpness, but more important, the shape at the transient edges- the ringing is getting in my way. I understand that ringing to some extent is unavoidable, but how can I miminize it? Thank you, Keren


"Repairing" an out-of- focus picture

Started by Nitram in comp.dsp9 years ago 25 replies

Hi, My question might be simplistic as neither optics nor image processing is my field. Firstly, I was wondering if it is possible to...

Hi, My question might be simplistic as neither optics nor image processing is my field. Firstly, I was wondering if it is possible to compensate for a picture taken by an out-of-focus digital camera by doing a 2D deconvolution on it (MMSE filtering or something like that), in order to recover the in-focus picture Secondly, can the optical transfer function between a properly focused pi...


Deconvolution problem

Started by niuer in comp.dsp11 years ago 4 replies

Hi guys, I have a theoretical relationship that variable z = convolution(x, y ). I now have vectors of z and x and I am trying to deconvolute...

Hi guys, I have a theoretical relationship that variable z = convolution(x, y ). I now have vectors of z and x and I am trying to deconvolute them to get vector y. I tried to to FFT to solve for y. The problem is that I also got some oscillation in the y vector while there should be none. The shape of the vectors z and x all look like bell shape and they look pretty smooth. They are close to z...


Problem with image deconvolution

Started by Tduell in comp.dsp9 years ago 1 reply

Hullo All, I recently posted to this group on this question but I never saw it appear, so please excuse my posting again. I have two...

Hullo All, I recently posted to this group on this question but I never saw it appear, so please excuse my posting again. I have two overlapping images (apprx. 30% overlap) which are part of a series to be stitched into a panorama. One image is blurred by motion blur, the other is sharp. As I effectively have the blurred and the 'latent' images it seemed like there was a fair chance I could...


Lytro

Started by glen herrmannsfeldt in comp.dsp8 years ago 2 replies

After seeing discussino of the Lytro light-field camera, the first thought I had was that DSP would be pretty important in making it work. Yet I...

After seeing discussino of the Lytro light-field camera, the first thought I had was that DSP would be pretty important in making it work. Yet I don't remember seeing any discussion of it. The article describing the technology is: http://graphics.stanford.edu/papers/lfcamera/lfcamera-150dpi.pdf it would seem to me that deconvolution would be related to the technology, though so far, (a...


Re: deconvolution in time?

Started by Anonymous in comp.dsp14 years ago 1 reply

Gordon Sande wrote: > On 2005-11-08 09:41:43 -0400, abariska@student.ethz.ch said: .=2E. > There are two common usages of adjoint. > > ...

Gordon Sande wrote: > On 2005-11-08 09:41:43 -0400, abariska@student.ethz.ch said: .=2E. > There are two common usages of adjoint. > > One is in matrix theory where it is the transpose of the matrix of cofact= ors > as one would find near the definition of determinants and how to solve > equations using determinants. I just looked through all my pure linear algebra books (Lang, J=E4nich


Deconvolution question

Started by Les Cargill in comp.dsp11 years ago 3 replies

Suppose I have an acoustic guitar with a (relatively good-sounding) peizo pickup (a K&K, for those interested). I can mic the guitar and...

Suppose I have an acoustic guitar with a (relatively good-sounding) peizo pickup (a K&K, for those interested). I can mic the guitar and record the peizo simultaneously. But when I deconvolve the miked signal against the peizo, the resulting convolution signature isn't very coherent. Most convolution signatures of this nature have a "spike" where the dominant bucket is - this has just a ...


vibroseis deconvolution without the reference sweep

Started by namespace in comp.dsp13 years ago 1 reply

I have a vibroseis dataset which has been collected in the field. To my knowledge, the recorded signal s'[t] is the convolution of the...

I have a vibroseis dataset which has been collected in the field. To my knowledge, the recorded signal s'[t] is the convolution of the original sweep s[t] and the reflection response r[t] of the layered earth. Thus, the relationship is expressed in its simplest form as s'[t] = s[t]*r[t], neglecting the effects of earth attenuation and noise. However, I do not have the reference sweep s[t] since...


deconvolution using known set of filters

Started by riz in comp.dsp12 years ago 3 replies

i have lot of filters impulse responses and signal 'x' that i got by convolving original signal 's' with one of the filter...

i have lot of filters impulse responses and signal 'x' that i got by convolving original signal 's' with one of the filter impulse response.Also,the signal 'x' contains noise. Now i want to recover the original signal 's'. 1)Which techniques are most feasible and effective to solve this problem 2)which technique is more real time


Discrete Deconvolution

Started by Anonymous in comp.dsp13 years ago 4 replies

Hello, all. I have a dilemma. I'm analyzing some time signals for periodicities, and I was wondering about a seemingly basic method of doing...

Hello, all. I have a dilemma. I'm analyzing some time signals for periodicities, and I was wondering about a seemingly basic method of doing it. I hope you'll forgive my ignorance, as my specialty is physics and not signal processing :P So, we have a time-series that is the product of a source signal and a window function : c(t_i) = w(t_i)s(t_i) where t_i represents the i_th time...


Which algorithm would you choose?

Started by John McDermick in comp.dsp9 years ago 2 replies

Say you have two signals, x and y, where y is the output of an unknown FIR filter. The only thing which is "known" about the FIR filter is that...

Say you have two signals, x and y, where y is the output of an unknown FIR filter. The only thing which is "known" about the FIR filter is that it has N filter coefficients. The above relates to acoustic echo cancellation for speech signals sampled at 8kHz. I guess you can call it a channel estimation problem? Or a deconvolution problem? I don't know.... Anyways....As a pre-liminary expe...


Mixed phase deconvolution

Started by Andreas in comp.dsp13 years ago 1 reply

Hello all DSP gurus, I am struggling with some (seismic) DSP theory and need some help! In seismic the convolutional model states that the...

Hello all DSP gurus, I am struggling with some (seismic) DSP theory and need some help! In seismic the convolutional model states that the observed signal as a function of time, st (seismic trace), equals the convolution between the seismic shot signal, s, and the earth response function, e: st=s*e. Given a known st and s I want to calculate the unknown e. We introduce a pulse shaping fi...