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Brian Slesinsky
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Published
Notes on Digital Signal Processing
By
Brian Slesinsky
Edited
May 2, 2022
2 stars
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pulseTrain
=
{
const
a
=
Array
(
600
)
;
for
(
let
i
=
0
;
i
<
a
.
length
;
i
++
)
{
a
[
i
]
=
(
(
i
-
i
%
100
)
/
100
)
%
2
==
1
?
1
:
0
;
}
return
a
;
}
Insert cell
impulseResponse
=
{
const
a
=
Array
(
100
)
;
let
area
=
0
;
for
(
let
i
=
0
;
i
<
100
;
i
++
)
{
const
phase
=
i
*
2
*
Math
.
PI
/
200
;
a
[
i
]
=
Math
.
sin
(
phase
)
;
area
+=
a
[
i
]
;
}
// normalize so that area under the curve is 1:
for
(
let
i
=
0
;
i
<
a
.
length
;
i
++
)
{
a
[
i
]
=
a
[
i
]
/
area
;
}
return
a
;
}
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convolution
=
convolute
(
pulseTrain
,
impulseResponse
)
;
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slowerPulseTrain
=
{
const
a
=
Array
(
600
)
;
for
(
let
i
=
0
;
i
<
a
.
length
;
i
++
)
{
a
[
i
]
=
(
(
i
-
i
%
150
)
/
150
)
%
2
==
1
?
1
:
0
;
}
return
a
;
}
Insert cell
slowerConvolution
=
convolute
(
slowerPulseTrain
,
impulseResponse
)
;
Insert cell
function
convolute
(
a
,
b
)
{
let
result
=
Array
(
a
.
length
+
b
.
length
)
.
fill
(
0
)
;
a
.
forEach
(
(
sample
,
i
)
=>
{
b
.
forEach
(
(
weight
,
j
)
=>
{
result
[
i
+
j
]
+=
sample
*
weight
;
}
)
;
}
)
;
return
result
;
}
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pulseTrain
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