Here is the problem. I want to write a convolution for two simple signals x[n]=0.2^n*u[n] and h[n]=u[n+2] for some values of n. This is how I implement it:
using Plots, DSP
x(n) = if n<0 0 else 0.2^n end
h(n) = if n<-2 0 else 1 end
n = -10:10
conv(h.(n),x.(n))
It doesn't work. Here is the error:
`float` not defined on abstractly-typed arrays; please convert to a more specific type
Any idea how may I fix it?
I ran it fine with a fresh REPL session:
julia> using Plots, DSP
[ Info: Precompiling Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80]
[ Info: Precompiling DSP [717857b8-e6f2-59f4-9121-6e50c889abd2]
julia> x(n) = if n<0 0 else 2^n end
x (generic function with 1 method)
julia> h(n) = if n<-2 0 else 1 end
h (generic function with 1 method)
julia> n = -10:10
-10:10
julia> conv(h.(n),x.(n))
41-element Array{Int64,1}:
0
0
(etc)
1984
1920
1792
1536
1024
julia> plot(conv(h.(n),x.(n)))
(plots ok)
If you change the 2 in 2^n to a float you need to specify Float64:
julia> x(n) = if n<0 0 else 0.2^n end
x (generic function with 1 method)
julia> conv(h.(n),Float64.(x.(n)))
41-element Array{Float64,1}:
0.0
8.458842092382145e-17
2.5376526277146434e-16
4.229421046191072e-17
2.1147105230955362e-16
(etc)
7.997440000004915e-5
1.597440000003685e-5
3.1744000002024485e-6
6.144000000924524e-7
1.0240000015600833e-7
