newlind
Design linear layer
Syntax
net = newlind(P,T,Pi)
Description
net = newlind(P,T,Pi) takes these input arguments,
P |
|
T |
|
Pi |
|
where each element Pi{i,k} is an
Ri-by-Q matrix, and the default = [];
and returns a linear layer designed to output T (with minimum sum square
error) given input P.
newlind(P,T,Pi) can also solve for linear networks with input delays and
multiple inputs and layers by supplying input and target data in cell array form:
P |
| Each element |
T |
| Each element |
Pi |
| Each element |
and returns a linear network with ID input delays, Ni
network inputs, and Nl layers, designed to output T (with
minimum sum square error) given input P.
Examples
You want a linear layer that outputs T given P for
the following definitions:
P = [1 2 3]; T = [2.0 4.1 5.9];
Use newlind to design such a network and check its response.
net = newlind(P,T); Y = sim(net,P)
You want another linear layer that outputs the sequence T given the
sequence P and two initial input delay states Pi.
P = {1 2 1 3 3 2};
Pi = {1 3};
T = {5.0 6.1 4.0 6.0 6.9 8.0};
net = newlind(P,T,Pi);
Y = sim(net,P,Pi)
You want a linear network with two outputs Y1 and Y2
that generate sequences T1 and T2, given the sequences
P1 and P2, with three initial input delay states
Pi1 for input 1 and three initial delays states Pi2 for
input 2.
P1 = {1 2 1 3 3 2}; Pi1 = {1 3 0};
P2 = {1 2 1 1 2 1}; Pi2 = {2 1 2};
T1 = {5.0 6.1 4.0 6.0 6.9 8.0};
T2 = {11.0 12.1 10.1 10.9 13.0 13.0};
net = newlind([P1; P2],[T1; T2],[Pi1; Pi2]);
Y = sim(net,[P1; P2],[Pi1; Pi2]);
Y1 = Y(1,:)
Y2 = Y(2,:)
Algorithms
newlind calculates weight W and bias
B values for a linear layer from inputs P and targets
T by solving this linear equation in the least squares sense:
[W b] * [P; ones] = T
Version History
Introduced before R2006a