# How are two signals multiplied? And how is it different from convolving two signals?

Suppose that I have two signals $x[n] = \left\{2,4,1\right\}$ and $p[n] = \left\{5,1,8\right\}$ and I want to multiply them.

• How do you do that?
• How different is it from convolving two signals?

I understand that multiplication in one domain is equal to convolution in other domain. How do you choose as to what to use : multiplication or convolution?

• How different are apples and oranges? This part of the question is too broad, please specify what kind of difference interests you. – chirlu Aug 23 '13 at 7:02
• This is like asking "What's better, an umbrella or a hammer?" Depends what you're trying to do. – endolith Aug 23 '13 at 14:19
• Will Normal Time domain convolution result in frequency domain multiplication ? or it should be CIRCULAR CONVOLUTION ! Somewhere I read Property of Discrete Fourier Transform [DFT] if x(n) and h(n) are two time-domain signals, circular convolution between them x(n)©h(n) is equivalent to multiplication in the frequency domain. Because this property used in cyclic prefix for OFDMA systems. – rajez79 Aug 26 '13 at 16:45

Yes, you are correct. Multiplication in time domain means convolution in frequency domain and vice versa. Multiplying your signals $x[n]$ and $y[n]$ will give an output:

\begin{align} z[n]&=\{2\cdot 5, 4\cdot 1, 1\cdot 8\}\\ &= \{10, 4, 8\}\end{align}

Remember that this output is in time domain. When you convolve $x[n]$ and $y[n]$, you will get $z[n]$ in time domain as:

\begin{align} z[n]&=\{5\cdot 2, 5\cdot 4+1\cdot 2, 5\cdot 1+1\cdot 4+8\cdot 2, 1\cdot 1+8\cdot 4, 8\cdot 1\}\\ &= \{10,22,25,33,8\} \end{align}

Just flip one of the signals around zero and start moving right one place at a time. Multiply the corresponding points as you go along. The output has a larger sequence because convolution output has ${\rm length}(x)+{\rm length}(y)-1$ points.

To answer your query about where to use multiplication & convolution, assume you want to pass signal $x(n)$ through filter $y(n)$. The output of the filter $z(n)$ will be convolution of $x(n)$ and $y(n)$.
Now assume that you first converted from time to frequency domain, i.e. $X(e^{i\omega})$ and $Y(e^{i\omega})$ are frequency domain representation of $x(n)$ and $y(n)$. Now, to find $Z(e^{i\omega})$(output in frequency domain), you have to multiply $X(e^{i\omega})$ and $Y(e^{i\omega})$. To get the output in time domain i.e. $z(n)$ you have to apply inverse transform.

So that's how you use convolution and multiplication.

• So when to use multiplication and when to use convolution? From what you explained convolution is equal to polynomial multiplication. – user2381442 Aug 23 '13 at 7:24
• @user2381442 edited the answer to include your query. And yes, convolution is a polynomial multiplication operation – KharoBangdo Aug 23 '13 at 8:17
• Convolution is filtering in the spatial domain, multiplication is filtering in the Fourier domain. What to use depends on what you are trying to do. – geometrikal Aug 23 '13 at 8:17