Smooth Signal Correlation

Specific Domains Optimization (Mathematical)
3

hi mr. odow, yes gladly: :leaves:

data - vector of floats

new signal is

y[1]=x1[1]*data[1]+x1[2]*data[2]

attribute (obj function) is

maxumize sum
tanh(x2[1]*y[i-1]) * y[i]

complex goal is
tanh(x2[1]*y[i-1]+x2[2]*y[i-2]+ ... ) * y[i])

so it is simplified, but its based on good core

using JuMP
using Ipopt

model = Model(Ipopt.Optimizer)

S=2 #
D=3 #line

@variable(model, x1[1:S])
@variable(model, x2[1:D])

@NLexpressions(model, begin
        y[i=1:3000], sum(data[2*(i-1)+1+j]* x1[j+1] for j=0:1    )
    end)



@NLobjective(
        model,
        Max,
         sum( tanh(x2[1]*y[i]    ) *y[i+1]            for i = 3:100   )  #just for 100 points
)


optimize!(model)
print(objective_value(model))
1 Like