Matlab+signal processing question -finding output signal using FRF

In summary, the goal is to find a way to make the input data and frequency response function vectors the same size in order to accurately estimate the output data. This can be achieved through methods such as FFT or interpolation, where the frequencies or time intervals are adjusted to match between the two vectors. Additionally, convolving the time domain vectors can also be an option.
  • #1
berdan
32
0
So,I got this vector of input data in Matlab,which is vector of approx 1x25000 length.
I have frequency responce function attained by different estimators (H1,H2,Arx).
Anyway,my FRF is also a vector of 1x129 length.

Those two are different sized vectors.How should I find the output data using input data and this obtained FRF vector?

One way is to transform input vector (which is sampled data) with FFT ,and then just multiply input vector with FRF,element by element = X(i)*Y(u) .But those two vectors would be different sizes,how should I make them both same size?
What is the correct approach in this case?I remember learning something about zero padding,how is it done?

Second way is transform FRF (IFFT) into time domain vector,and then convolve those two vectors.But again,those two will be different sized vectors,how should I do it?

Thanks in advance!
 
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  • #2
You need to be a little more specific. Is the input data a time domain signal where you want to estimate the output from the frequency response function? Or is the input in the frequency domain as well? Do the 129 points of your FRF cover the entire frequency band of the function eventually?
 
  • #3
berdan said:
One way is to transform input vector (which is sampled data) with FFT ,and then just multiply input vector with FRF,element by element = X(i)*Y(u) .But those two vectors would be different sizes,how should I make them both same size?

Second way is transform FRF (IFFT) into time domain vector,and then convolve those two vectors.But again,those two will be different sized vectors

The two vectors need to have the same frequency intervals in option 1, or the same time intervals in option 2.

For example if you have a table of values of the FRF (amplitude and phase at each frequency), you could fit a curve through the data and interpolate for different frequencies.
 

1. What is Matlab and how is it used in signal processing?

Matlab is a programming language and software environment commonly used in scientific and engineering applications. It is particularly useful for signal processing tasks such as analyzing and manipulating digital signals.

2. What is a FRF and how is it used in signal processing?

FRF stands for Frequency Response Function. It is a mathematical representation that describes the relationship between the input and output signals of a system at different frequencies. In signal processing, FRF is used to analyze the frequency response of a system and design filters or other signal processing techniques.

3. How can I use Matlab to find the output signal using FRF?

To find the output signal using FRF in Matlab, you can use the freqz function. This function takes in the input signal and the FRF as parameters and calculates the output signal. You can also use the filter function to apply the FRF to the input signal.

4. Can Matlab be used for real-time signal processing?

Yes, Matlab can be used for real-time signal processing. It has tools and functions specifically designed for real-time processing, such as the realtime and audiorecorder functions. However, the real-time performance may depend on the hardware and processing speed of the computer.

5. Are there any resources available for learning Matlab and signal processing?

Yes, there are many resources available for learning Matlab and signal processing. You can find tutorials and documentation on the official Matlab website, as well as online courses and videos on websites like Coursera and YouTube. There are also textbooks and reference books available for purchase.

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