Convolution of Signals: High & Low Frequency Effects

In summary, the conversation discusses the concept of convolving signals and its effect on frequency signals. It is mentioned that convolving two high frequency signals may result in a high frequency signal, while convolving two low frequency signals may result in a low frequency signal. It is also mentioned that convolving a low and high frequency signal may result in a low frequency signal, according to intuition. The conversation also clarifies the meaning of "convolve" and mentions that it is similar to correlation.
  • #1
boredaxel
19
0
Will we get a high frequency signal from convolving 2 high frequency signals?

Also will we get a low frequency signal from convolving 2 low frequency signals?

How about convolving one low and one high frequency signal? My intuition tells me its low frequency signal.

Thanks for any guidance on this
 
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  • #2
I don't know the word "convolve" and it isn't in my dictionary.

Do you mean "mix" or "mixing" ?
 
  • #3
vk6kro said:
I don't know the word "convolve" and it isn't in my dictionary.

do you know what "convolution", as applied to signals, is?

anyway, to answer the OP, if you convolve a high frequency signal against a low frequency signal, if the two signals have little in common, what you'll get out is close to zero. convolution is the same as correlation except that one of the signals is reversed.
 

FAQ: Convolution of Signals: High & Low Frequency Effects

1. What is convolution of signals?

Convolution of signals is a mathematical operation that combines two signals to create a new signal. It is used to analyze the effects of one signal on another and is commonly used in signal processing and image processing applications.

2. How does high frequency affect convolution of signals?

High frequency signals can have a significant impact on the convolution process. If the high frequency components of one signal are not well-matched with the other signal, it can result in distortions or artifacts in the convolved signal. This is why it is important to carefully analyze and adjust the high frequency components before performing a convolution.

3. What are the effects of low frequency on convolution of signals?

Low frequency signals also play an important role in convolution. If there are significant differences in the low frequency components of the two signals being convolved, it can result in a blurred or smoothed out convolved signal. To avoid this, it is important to carefully adjust the low frequency components before performing convolution.

4. Can convolution of signals be used to remove noise?

Yes, convolution can be used to remove noise from a signal. This is done by convolving the noisy signal with a filter kernel that is specifically designed to remove the unwanted noise. The resulting convolved signal will have reduced noise and improved signal clarity.

5. What are some real-world applications of convolution of signals?

Convolution of signals has a wide range of real-world applications, including image and audio processing, signal filtering, and pattern recognition. It is also used in fields such as computer vision, telecommunications, and biomedical engineering. Some specific examples include noise reduction in images, speech enhancement, and feature extraction in facial recognition systems.

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