# Can you present the convolution of sinusoidal with itself?

Ladies, Gentlemen, Because I am homeless (in France), and get internet access only in public libraries with many restrictions in timing etc, I can not write down even a simple convolution. So I ask you post here the convolution of some sinusoidal function with itshelf.

For example: 0.951056516295, 0.587785252292, -0.587785252292, -0.951056516295, 0.

Regards

• that doesn't look like a sinusoid Nov 18 '15 at 14:52
• Can you convince the library to install a program such as SciLab on their computers? It is free, and its development is supported by INRIA. Having access to such a tool would be very helpful in your research. See scilab.org
– MBaz
Nov 18 '15 at 18:07

For your data points I get:

-2.467162e-16 -9.045085e-01 -1.118034e+00 7.725425e-01 2.500000e+00 7.725425e-01 -1.118034e+00 -9.045085e-01 -1.480297e-16

from

#27154
data <- c(0.951056516295, 0.587785252292, -0.587785252292, -0.951056516295, 0.)
output <- convolve(data,data, type ="open")

• Mr Peter K., many thanks for your immediate response. My output agree with yours. Indeed -2.467162e-16 and -1.480297e-16 are zeros. Regards Nov 18 '15 at 15:36

I sent my question from municipal library of saint Claude, France where they offered me just one hour. ow I am in CCAS of the same town where they offer more time, so I will try answer my question.

1) 0.951056516295x0=0 + 0.587785252292x0=0 + -0.587785252292x0=0 + -0.951056516295x0=0 + 0x0.951056516295=0

total = 0

2) 0.951056516295x0=0 + 0.587785252292x0=0 + -0.587785252292x0=0 + -0.951056516295x0.951056516295=-0.9045084971871816 + 0x0.587785252292=0 total = -0.9045

3) 0.951056516295x0=0 + 0.587785252292x0=0 + -0.587785252292x0.951056516295=-0.559 + -0.951056516295x0.587785252292=-0.559 + 0x-0.587785252292=0

total = -1.118

4) 0.951056516295x0=0 + 0.587785252292x0.951056516295=0.559 + -0.587785252292x0.587785252292=-0.3454915 + -0.951056516295x-0.587785252292=0.559 + 0x-0.951056516295=0

total = 0.7725

5) 0.951056516295x0.951056516295=0.9045 + 0.587785252292x0.587785252292=0.3454915 + -0.587785252292x-0.587785252292=0.3454915 + -0.951056516295x-0.951056516295=0.9045 + 0x0=0

total = 2.5

6) 0x0.951056516295=0 + 0.951056516295x0.587785252292=0.559 + 0.587785252292x-0.587785252292=-0.3454915 + -0.587785252292x-0.951056516295=0.559 + -0.951056516295x0=0

total = 0.7725

7) 0x0.951056516295=0 + 0x0.587785252292=0 + 0.951056516295x-0.587785252292=-0.559 + 0.587785252292x-0.951056516295=-0.559 + -0.587785252292x0=0

total = -1.118

8) 0x0.951056516295=0 + 0x0.587785252292=0 + 0x-0.587785252292=0 + 0.951056516295x-0.951056516295=-0.9045 + 0.587785252292x0=0 + -0.587785252292x0=0 + -0.951056516295x0=0 + 0x0=0

total = -0.9045

9) 0x0.951056516295=0 + 0x0.587785252292=0 + 0x-0.587785252292=0 + 0x-0.951056516295=0 + 0x0=0

total = 0

output: 0, -0.9045, -1.118, 0.7725, 2.5, 0.7725, -1.118, -0.9045, 0.

Regards

• Interesting is 5th summation for samples multiplied themselves (are squared) and sum gets maximum (2.5). Regards Nov 19 '15 at 7:43