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X = [1 0 ; 2 1 ]; %Declaramos matriz x | |
Y = [1 0 ]; %Declaramos matriz y | |
observmatrix = obsv(X,Y) %Aplicamos el comando obsv para obtenermatriz de observabilidad | |
det(observmatrix) %Obtenemos el determinante |
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#!/usr/bin/python | |
#Adan Silva | |
from random import * | |
from numpy import * | |
from numpy.random import * | |
from sys import argv | |
#Tasa de entrenamiento |
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function matrizganancia | |
A=[0 1 0;0 0 1;-1 -5 -6]; %Declaramos la matriz A | |
B=[0;1;1;]; %Declaramos la matriz B | |
p=[-2+j*4 -2-j*4 -10]; %Declaramos el vector p de los eigenvalores | |
K=place(A,B,p) %Aplicamos el comando 'place' con la sintaxis F = place (A, B, P) |
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import snakes.plugins | |
snakes.plugins.load('gv', 'snakes.nets', 'nets') | |
from nets import * | |
n = PetriNet('N') #creando una red petri | |
n.add_place(Place('v0')) #declarando estado inicial reposo del abanico | |
n.add_transition(Transition('t0')) #declarar primera transicion al accionar interruptor | |
n.add_place(Place('v1')) #declarando estado de velocidad uno del abanico | |
n.add_transition(Transition('t1')) #declarando segunda transicion al accionar el interruptor otra vez |